How to Cite This Stats-of-1 Resources Webpage

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How to Add Resources

See this post for instructions on how to submit your own suggested resources and references: https://statsof1.org/2021-09-03-adding-new-esametric-resources/

The following esametric resources are ordered alphabetically, stratified by category. Note that some items are listed multiple times.

Actigraphy + Accelerometry

Publications

• Barnett I, Torous J, Staples P, Keshavan M, Onnela JP. Beyond smartphones and sensors: Choosing appropriate statistical methods for the analysis of longitudinal data. Journal of the American Medical Informatics Association. 2018 Dec;25(12):1669-74. academic.oup.com/jamia/article/25/12/1669/5110357
• Catellier DJ, Hannan PJ, Murray DM, Addy CL, Conway TL, Yang S, Rice JC. Imputation of missing data when measuring physical activity by accelerometry. Medicine and science in sports and exercise. 2005 Nov;37(11 Suppl):S555. ncbi.nlm.nih.gov/pmc/articles/PMC2435061
• Rowe DA, Mahar MT, Raedeke TD, Lore J. Measuring physical activity in children with pedometers: Reliability, reactivity, and replacement of missing data. Pediatric Exercise Science. 2004 Nov 1;16(4):343-54. researchgate.net/profile/David_Rowe/publication/251259986….pdf

Aggregated N-of-1 Analyses

This section covers Aggregated N-of-1, Intensive Longitudinal Data, Meta-analysis, Mixed/Random Effects Models, Multilevel/Hierarchical Models, Multilevel Time Series, Series-of-n-of-1.

Links

• Analyzing Intensive Longitudinal Data centerstat.org/analyzing-intensive-longitudinal-data/

Publications

• Araujo A, Julious S, Senn S. Understanding variation in sets of N-of-1 trials. PLoS One. 2016;11(12). ncbi.nlm.nih.gov/pmc/articles/PMC5131970
• Barnett I, Torous J, Staples P, Keshavan M, Onnela JP. Beyond smartphones and sensors: Choosing appropriate statistical methods for the analysis of longitudinal data. Journal of the American Medical Informatics Association. 2018 Dec;25(12):1669-74. academic.oup.com/jamia/article/25/12/1669/5110357
• Bauer SR, Breyer BN, Oni-Orisan A, Steinman MA, Sim I, McCulloch CE, Kenfield SA. PERSONAL: Feasibility Study Protocol for Placebo-Controlled, Randomized n-of-1 Trials of Tamsulosin for Lower Urinary Tract Symptoms. Frontiers in Digital Health. 2020 Jun 26;2:7. frontiersin.org/articles/10.3389/fdgth.2020.00007/full
• Beltz AM, Wright AG, Sprague BN, Molenaar PC. Bridging the nomothetic and idiographic approaches to the analysis of clinical data. Assessment. 2016 Aug;23(4):447-58. journals.sagepub.com/doi/abs/10.1177/1073191116648209
• Bergman LR. The interpretation of single individuals’ measurements. Journal for Person-Oriented Research. 2017;3(1):119. ncbi.nlm.nih.gov/pmc/articles/PMC7869697/
• Blackston JW, Chapple AG, McGree JM, McDonald S, Nikles J. Comparison of aggregated N-of-1 trials with parallel and crossover randomized controlled trials using simulation studies. Healthcare 2019 Dec (Vol. 7, No. 4, p. 137). Multidisciplinary Digital Publishing Institute. mdpi.com/2227-9032/7/4/137
• Chen X, Chen P. A comparison of four methods for the analysis of N-of-1 trials. PloS one. 2014 Feb 4;9(2):e87752. journals.plos.org/plosone/article?id=10.1371/journal.pone.0087752
• de Vries RM, Morey RD. Bayesian hypothesis testing for single-subject designs. Psychological methods. 2013 Jun;18(2):165. psycnet.apa.org/record/2013-06780-001
• Declercq L, Cools W, Beretvas SN, Moeyaert M, Ferron JM, Van den Noortgate W. MultiSCED: A tool for (meta-) analyzing single-case experimental data with multilevel modeling. Behavior research methods. 2020 Feb;52(1):177-92. link.springer.com/article/10.3758/s13428-019-01216-2
• Declercq L, Jamshidi L, Fernández-Castilla B, Beretvas SN, Moeyaert M, Ferron JM, Van den Noortgate W. Analysis of single-case experimental count data using the linear mixed effects model: A simulation study. Behavior Research Methods. 2019 Dec;51(6):2477-97. link.springer.com/article/10.3758/s13428-018-1091-y
• Fok CC, Ramsay JO. Fitting curves with periodic and nonperiodic trends and their interactions with intensive longitudinal data. Models for intensive longitudinal data. 2006 Jan 19:109-23. oxford.universitypressscholarship.com/view/10.1093/acprof:oso/9780195173444.001.0001/acprof-9780195173444
• Gates KM, Chow SM, Molenaar PCM. Intensive Longitudinal Analysis of Human Processes. Chapan and Hall/CRC; 2022 Dec 7. routledge.com/Analysis-of-Intra-Individual-Variation-Systems-Approaches-to-Human-Process/Gates-Chow-Molenaar/p/book/9781482230598
• Gärtner T, Schneider J, Arnrich B, Konigorski S. Comparison of Bayesian Networks, G-estimation and linear models to estimate causal treatment effects in aggregated N-of-1 trials with carry-over effects. BMC Medical Research Methodology. 2023 Aug 21;23(1):191. link.springer.com/article/10.1186/s12874-023-02012-5
• Goldstein H, Healy MJ, Rasbash J. Multilevel time series models with applications to repeated measures data. Statistics in medicine. 1994 Aug 30;13(16):1643-55. onlinelibrary.wiley.com/doi/abs/10.1002/sim.4780131605
• Golino H, Christensen AP, Nesselroade JR. Towards a psychology of individuals: the ergodicity information index and a bottom-up approach for finding generalizations 2022. doi:10.31234/osf.io/th6rm. psyarxiv.com/th6rm
• Grekov P, Pustejovsky JE, Klingbeil DA. Flexible distributional models for meta-analysis of reading fluency outcomes from single-case designs: An examination using Bayesian methods. jepusto.com/publications/Flexible-distributional-models-for-reading-outcomes/
• Hendrickson RC, Thomas RG, Schork N, Raskind MA. Optimizing aggregated N-of-1 trial designs for predictive biomarker validation: statistical methods and theoretical findings. Frontiers in Digital Health. 2020;2:13. frontiersin.org/articles/10.3389/fdgth.2020.00013
• Hyndman RJ, Athanasopoulos G, Shang HL. hts: An R Package for Forecasting Hierarchical or Grouped Time Series. R Package 2015. cran.r-project.org/web/packages/hts/vignettes/hts.pdf
• Kratochwill TR, Levin JR. Meta-and statistical analysis of single-case intervention research data: Quantitative gifts and a wish list. Journal of School Psychology. 2014 Apr 1;52(2):231-5. sciencedirect.com/science/article/pii/S0022440514000168
• Li H. Model selection of GLMMs in the analysis of count data in single-case studies: A Monte Carlo simulation. Behavior Research Methods. 2024 Jul 10:1-22. link.springer.com/article/10.3758/s13428-024-02464-7
• Li H, Luo W, Baek E. Multilevel modeling in single-case studies with zero-inflated and overdispersed count data. Behavior Research Methods. 2024 Feb 21:1-7. link.springer.com/article/10.3758/s13428-024-02359-7
• Li R, Root TL, Shiffman S. A local linear estimation procedure for functional multilevel modeling. Models for intensive longitudinal data. 2006 Jan 19:63-83. oxford.universitypressscholarship.com/view/10.1093/acprof:oso/9780195173444.001.0001/acprof-9780195173444
• Moeyaert M, Yang P, Xue Y, Lou Y. Imbalances in Two-Level Hierarchical Linear Modeling of Single-Case Data: A Monte Carlo Simulation Study. The Journal of Experimental Education. 2024 Aug 20:1-21. tandfonline.com/doi/abs/10.1080/00220973.2024.2394951
• Porcino AJ, Shamseer L, Chan AW, Kravitz RL, Orkin A, Punja S, Ravaud P, Schmid CH, Vohra S. Spirit extension and elaboration for n-of-1 trials: spent 2019 checklist. bmj. 2020 Feb 27;368. bmj.com/content/368/bmj.m122
• Qian T, Klasnja P, Murphy SA. Linear mixed models with endogenous covariates: modeling sequential treatment effects with application to a mobile health study. Statistical science: a review journal of the Institute of Mathematical Statistics. 2020;35(3):375. ncbi.nlm.nih.gov/pmc/articles/PMC7596885/
• Ridenour TA, Chen SH, Liu HY, Bobashev GV, Hill K, Cooper R. The clinical trials mosaic: toward a range of clinical trials designs to optimize evidence-based treatment. Journal for Person-Oriented Research. 2017;3(1):28-48. person-research.org/journal/files/3_1/filer/5.pdf
• Ridenour TA, Wittenborn AK, Raiff BR, Benedict N, Kane-Gill S. Illustrating idiographic methods for translation research: moderation effects, natural clinical experiments, and complex treatment-by-subgroup interactions. Translational behavioral medicine. 2016 Mar 1;6(1):125-34. ncbi.nlm.nih.gov/pmc/articles/PMC4807195/
• Shrestha S, Jain S. A Bayesian‐bandit adaptive design for N‐of‐1 clinical trials. Statistics in Medicine. 2021 Mar 30;40(7):1825-44. onlinelibrary.wiley.com/doi/abs/10.1002/sim.8873
• Stunnenberg BC, Woertman W, Raaphorst J, Statland JM, Griggs RC, Timmermans J, Saris CG, Schouwenberg BJ, Groenewoud HM, Stegeman DF, van Engelen BG. Combined N-of-1 trials to investigate mexiletine in non-dystrophic myotonia using a Bayesian approach; study rationale and protocol. BMC neurology. 2015 Dec;15(1):1-0. bmcneurol.biomedcentral.com/articles/10.1186/s12883-015-0294-4
• Sung L, Tomlinson GA, Greenberg ML, Koren G, Judd P, Ota S, Feldman BM. Serial controlled N-of-1 trials of topical vitamin E as prophylaxis for chemotherapy-induced oral mucositis in paediatric patients. European Journal of Cancer. 2007 May 1;43(8):1269-75. sciencedirect.com/science/article/abs/pii/S0959804907001268
• Tan X, Shiyko MP, Li R, Li Y, Dierker L. A time-varying effect model for intensive longitudinal data. Psychological methods. 2012 Mar;17(1):61. ncbi.nlm.nih.gov/pmc/articles/PMC3288551/
• Timms KP, Martín CA, Rivera DE, Hekler EB, Riley W. Leveraging intensive longitudinal data to better understand health behaviors. In2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2014 Aug 26 (pp. 6888-6891). IEEE. ieeexplore.ieee.org/abstract/document/6945211
• Van den Noortgate W, Onghena P. Combining single-case experimental data using hierarchical linear models. School Psychology Quarterly. 2003;18(3):325. psycnet.apa.org/record/2003-08719-005
• Walls TA, Schafer JL. Models for intensive longitudinal data. Oxford University Press; 2006 Jan 19. academic.oup.com/book/5915
• Zucker DR, Schmid CH, McIntosh MW, D’agostino RB, Selker HP, Lau J. Combining single patient (N-of-1) trials to estimate population treatment effects and to evaluate individual patient responses to treatment. Journal of clinical epidemiology. 1997 Apr 1;50(4):401-10. sciencedirect.com/science/article/abs/pii/S0895435696004295
• Zucker DR, Ruthazer R, Schmid CH. Individual (N-of-1) trials can be combined to give population comparative treatment effect estimates: Methodologic considerations. Journal of clinical epidemiology. 2010 Dec 1;63(12):1312-23. sciencedirect.com/science/article/abs/pii/S0895435610001940

Applications and Empirical Studies

Publications

• Daza EJ, Wac K, Oppezzo M. Effects of Sleep Deprivation on Blood Glucose, Food Cravings, and Affect in a Non-Diabetic: An N-of-1 Randomized Pilot Study. Healthcare 2020 Mar (Vol. 8, No. 1, p. 6). Multidisciplinary Digital Publishing Institute. mdpi.com/2227-9032/8/1/6
• DeLoatche KJ. Parent-child interaction therapy as a treatment for ADHD in early childhood: A multiple baseline single-case design. University of South Florida; 2015. core.ac.uk/download/pdf/71953292.pdf
• Dickerson E. Computerized Cognitive Remediation Therapy (CCRT): Investigating Change in the Psychosocial and Cognitive Function of Adolescent Psychiatric Patients. Northeastern University; 2016. repository.library.northeastern.edu/files/neu:cj82nb768/fulltext.pdf
• Lutz M. N-of-1 Trials and Analyzing Your Own Fitness Data: Do I really sleep worse after drinking alcohol? Towards Data Science. 2024 Apr 19. towardsdatascience.com/n-of-1-trials-and-analyzing-your-own-fitness-data-7ae390036094
• Matias I, Daza EJ, Wac K. What possibly affects nighttime heart rate? Conclusions from N-of-1 observational data. Digital Health. 2022 Aug 24. journals.sagepub.com/doi/10.1177/20552076221120725

Bayesian Approaches

Publications

• Batley PN, Hedges LV. Accurate models vs. accurate estimates: A simulation study of Bayesian single-case experimental designs. Behavior Research Methods. 2021 Feb 11:1-7. link.springer.com/article/10.3758/s13428-020-01522-0
• Colopy GW, Roberts SJ, Clifton DA. Bayesian optimization of personalized models for patient vital-sign monitoring. IEEE journal of biomedical and health informatics. 2017 Dec 19;22(2):301-10. ieeexplore.ieee.org/abstract/document/8226743
• Colopy GW, Roberts SJ, Clifton DA. Gaussian processes for personalized interpretable volatility metrics in the step-down ward. IEEE journal of biomedical and health informatics. 2019 Jan 22;23(3):949-59. ieeexplore.ieee.org/abstract/document/8621007
• Gärtner T, Schneider J, Arnrich B, Konigorski S. Comparison of Bayesian Networks, G-estimation and linear models to estimate causal treatment effects in aggregated N-of-1 trials with carry-over effects. BMC Medical Research Methodology. 2023 Aug 21;23(1):191. link.springer.com/article/10.1186/s12874-023-02012-5
• Grekov P, Pustejovsky JE, Klingbeil DA. Flexible distributional models for meta-analysis of reading fluency outcomes from single-case designs: An examination using Bayesian methods. jepusto.com/publications/Flexible-distributional-models-for-reading-outcomes/
• Lum K, Dunson DB, Johndrow J. Closer than they appear: A Bayesian perspective on individual-level heterogeneity in risk assessment. arXiv preprint arXiv:2102.01135. 2021 Feb 1. arxiv.org/abs/2102.01135
• Natesan P, Hedges LV. Bayesian unknown change-point models to investigate immediacy in single case designs. Psychological Methods. 2017 Dec;22(4):743. psycnet.apa.org/doiLanding?doi=10.1037%2Fmet0000134 (pdf)
• Natesan Batley P, Shukla Mehta S, Hitchcock JH. A Bayesian rate ratio effect size to quantify intervention effects for count data in single case experimental research. Behavioral Disorders. 2020 Jun 19:0198742920930704. journals.sagepub.com/doi/abs/10.1177/0198742920930704 (pdf)
• Pascual C, Diaz K, Jain S. Multivariate variable selection in N-of-1 observational studies via additive Bayesian networks. Plos one. 2024 Aug 26;19(8):e0305225. journals.plos.org/plosone/article?id=10.1371/journal.pone.0305225
• Senarathne SG, Overstall AM, McGree JM. Bayesian adaptive N‐of‐1 trials for estimating population and individual treatment effects. Statistics in Medicine. 2020 Dec 20;39(29):4499-518. onlinelibrary.wiley.com/doi/abs/10.1002/sim.8737
• Shrestha S, Jain S. A Bayesian‐bandit adaptive design for N‐of‐1 clinical trials. Statistics in Medicine. 2021 Mar 30;40(7):1825-44. onlinelibrary.wiley.com/doi/abs/10.1002/sim.8873
• Stunnenberg BC, Woertman W, Raaphorst J, Statland JM, Griggs RC, Timmermans J, Saris CG, Schouwenberg BJ, Groenewoud HM, Stegeman DF, van Engelen BG. Combined N-of-1 trials to investigate mexiletine in non-dystrophic myotonia using a Bayesian approach; study rationale and protocol. BMC neurology. 2015 Dec;15(1):1-0. bmcneurol.biomedcentral.com/articles/10.1186/s12883-015-0294-4
• Sung L, Tomlinson GA, Greenberg ML, Koren G, Judd P, Ota S, Feldman BM. Serial controlled N-of-1 trials of topical vitamin E as prophylaxis for chemotherapy-induced oral mucositis in paediatric patients. European Journal of Cancer. 2007 May 1;43(8):1269-75. sciencedirect.com/science/article/abs/pii/S0959804907001268
• Zhu T, Colopy GW, Pugh CW, Clifton DA. Personalised patient monitoring in haemodialysis using hierarchical Gaussian processes. Institute of Electrical and Electronics Engineers. ora.ox.ac.uk/objects/uuid:f9cc27d2-d47a-45f5-8f7a-a3a8f792b303

Causality + Causal Inference + Mediation Analysis

Publications

• Anjum RL, Copeland S, Rocca E. Rethinking Causality, Complexity and Evidence for the Unique Patient: A CauseHealth Resource for Healthcare Professionals and the Clinical Encounter. Springer Nature. 2020. library.oapen.org/handle/20.500.12657/39574
• Balandat M. New tools for econometric analysis of high-frequency time series data-application to demand-side management in electricity markets. University of California, Berkeley; 2016. search.proquest.com/openview/17ecbcf034eb521b90b63a6fe9c8a314/1?pq-origsite=gscholar&cbl=18750
• Bojinov I, Rambachan A, Shephard N. Panel experiments and dynamic causal effects: A finite population perspective. Quantitative Economics. 2021 Nov;12(4):1171-96. onlinelibrary.wiley.com/doi/full/10.3982/QE1744
• Bojinov I, Shephard N. Time series experiments and causal estimands: exact randomization tests and trading. Journal of the American Statistical Association. 2019 Oct 2;114(528):1665-82. tandfonline.com/doi/abs/10.1080/01621459.2018.1527225
• Bojinov I, Simchi-Levi D, Zhao J. Design and analysis of switchback experiments. Management Science. 2023 Jul;69(7):3759-77. pubsonline.informs.org/doi/abs/10.1287/mnsc.2022.4583
• Cai X, Zeng L, Fowler C, Dixon L, Ongur D, Baker JT, Onnela JP, Valeri L. Causal estimands and identification of time-varying effects in non-stationary time series from N-of-1 mobile device data. arXiv preprint arXiv:2407.17666. 2024 Jul 24. arxiv.org/abs/2407.17666
• Cook TD, Campbell DT, Shadish W. Experimental and quasi-experimental designs for generalized causal inference. Boston, MA: Houghton Mifflin; 2002. onlinelibrary.wiley.com/doi/10.1002/pam.10129
• Daza EJ. Person as Population: A Longitudinal View of Single-Subject Causal Inference for Analyzing Self-Tracked Health Data. arXiv preprint arXiv:1901.03423. 2019 Jan 10. arxiv.org/abs/1901.03423
• Daza EJ. Causal analysis of self-tracked time series data using a counterfactual framework for N-of-1 trials. Methods of information in medicine. 2018 Feb;57(Suppl 1):e10. thieme-connect.de/products/ejournals/html/10.3414/ME16-02-0044
  • LaTeX pre-print (identical content) here
• Daza EJ, Matias I, Schneider L. Model-Twin Randomization (MoTR) for Estimating One’s Own Recurring Individual Treatment Effect. Statistics in Medicine. 2024 Oct 1 under review. arxiv.org/abs/2208.00739 (2-min explainer video here)
• Eichler M. Causal inference in time series analysis. Causality: Statistical perspectives and applications. 2012 Jul 13:327-54. onlinelibrary.wiley.com/doi/book/10.1002/9781119945710
• Gärtner T, Schneider J, Arnrich B, Konigorski S. Comparison of Bayesian Networks, G-estimation and linear models to estimate causal treatment effects in aggregated N-of-1 trials with carry-over effects. BMC Medical Research Methodology. 2023 Aug 21;23(1):191. link.springer.com/article/10.1186/s12874-023-02012-5
• Hall GJ, Putzeys S, Kratochwill TR, Levin JR. Discovering Internal Validity Threats and Operational Concerns in Single-Case Experimental Designs Through Directed Acyclic Graphs. Educational Psychology Review. 2024 Dec;36(4):128. link.springer.com/article/10.1007/s10648-024-09962-2
• Han K, Basse G, Bojinov I. Population interference in panel experiments. Journal of Econometrics. 2024 Jan 1;238(1):105565. sciencedirect.com/science/article/pii/S0304407623002816
• Izem R, McCarter R. Randomized and non-randomized designs for causal inference with longitudinal data in rare disorders. Orphanet Journal of Rare Diseases. 2021 Dec;16:1-9. ojrd.biomedcentral.com/articles/10.1186/s13023-021-02124-5
• Krajewski T, Hudgens M. The augmented synthetic control method in public health and biomedical research. Statistical Methods in Medical Research. 2024 Feb 6:09622802231224638. journals.sagepub.com/doi/full/10.1177/09622802231224638
• Langenberg B, Wurpts IC, Geuke GG, Onghena P. Estimating and Testing Causal Mediation Effects in Single-Case Experimental Designs Using State-Space Modeling. Evaluation & the Health Professions. 2022:01632787211067533. journals.sagepub.com/doi/10.1177/01632787211067533
• Linden A. A matching framework to improve causal inference in interrupted time‐series analysis. Journal of Evaluation in Clinical Practice. 2018 Apr;24(2):408-15. onlinelibrary.wiley.com/doi/abs/10.1111/jep.12874
• MacKinnon DP, Smyth HL, Somers J, Ho E, Norget J, Miočević M. A randomization permutation test for single subject mediation. Evaluation & the health professions. 2022 Mar;45(1):54-65. journals.sagepub.com/doi/10.1177/01632787211070811
• Mahoney J. Strategies of causal inference in small-N analysis. Sociological methods & research. 2000 May;28(4):387-424. journals.sagepub.com/doi/abs/10.1177/0049124100028004001
• Mahoney J. Toward a unified theory of causality. Comparative Political Studies. 2008 Apr;41(4-5):412-36. journals.sagepub.com/doi/abs/10.1177/0010414007313115
• Malenica I, Bibaut A, van der Laan MJ. Adaptive Sequential Design for a Single Time-Series. arXiv preprint arXiv:2102.00102. 2021 Jan 29. arxiv.org/abs/2102.00102
• Matias I, Daza EJ, Wac K. What possibly affects nighttime heart rate? Conclusions from N-of-1 observational data. Digital Health. 2022 Aug 24. journals.sagepub.com/doi/10.1177/20552076221120725
• Menchetti F, Cipollini F, Mealli F. Combining counterfactual outcomes and ARIMA models for policy evaluation. The Econometrics Journal. 2023 Jan;26(1):1-24. academic.oup.com/ectj/article/26/1/1/6713620
  • R package: github.com/FMenchetti/CausalArima
• Nagesh N, Azimi I, Andriola T, Rahmani AM, Jain R. Towards Deep Personal Lifestyle Models Using Multimodal N-of-1 Data. InInternational Conference on Multimedia Modeling 2023 Jan 9 (pp. 589-600). Cham: Springer International Publishing. link.springer.com/chapter/10.1007/978-3-031-27077-2_46
• Neto EC, Bot BM, Perumal T, Omberg L, Guinney J, Kellen M, Klein A, Friend SH, Trister AD. Personalized hypothesis tests for detecting medication response in Parkinson disease patients using iPhone Sensor data. InBiocomputing 2016: Proceedings of the Pacific Symposium 2016 (pp. 273-284). ncbi.nlm.nih.gov/pubmed/26776193
• Neto EC, Prentice RL, Bot BM, Kellen M, Friend SH, Trister AD, Omberg L, Mangravite L. Towards personalized causal inference of medication response in mobile health: an instrumental variable approach for randomized trials with imperfect compliance. arXiv preprint arXiv:1604.01055. 2016 Apr 4. arxiv.org/abs/1604.01055
• Neto EC, Tummalacherla M, Mangravite L, Omberg L. Causality-based tests to detect the influence of confounders on mobile health diagnostic applications: a comparison with restricted permutations. arXiv. 2019 Nov:arXiv-1911. arxiv.org/abs/1911.05139
• Piccininni M, Stensrud MJ, Shahn Z, Konigorski S. Causal inference for N-of-1 trials. arXiv preprint arXiv:2406.10360. 2024 Jun 14. arxiv.org/abs/2406.10360
• Qu K, Schmid CH, Liu T. Instrumental Variable Approach to Estimating Individual Causal Effects in N-of-1 Trials: Application to ISTOP Study. arXiv preprint arXiv:2306.14019. 2023 Jun 24. arxiv.org/abs/2306.14019
• Rohlfing I. Case studies and causal inference: An integrative framework. Palgrave Macmillan; 2012 Sep 26. link.springer.com/book/10.1057/9781137271327
  • 2013 review by Martino Maggetti: onlinelibrary.wiley.com/doi/full/10.1111/spsr.12063
• Runge J, Gerhardus A, Varando G, Eyring V, Camps-Valls G. Causal inference for time series. Nature Reviews Earth & Environment. 2023 Jul;4(7):487-505. nature.com/articles/s43017-023-00431-y
• van der Laan MJ, Malenica I. Robust Estimation of Data-Dependent Causal Effects based on Observing a Single Time-Series. arXiv preprint arXiv:1809.00734. 2018 Sep 3. arxiv.org/abs/1809.00734
• Wu X, Weinberger KR, Wellenius GA, Dominici F, Braun D. Assessing the causal effects of a stochastic intervention in time series data: Are heat alerts effective in preventing deaths and hospitalizations?. arXiv preprint arXiv:2102.10478. 2021 Feb 20. arxiv.org/abs/2102.10478

Changepoint Approaches

Publications

• Batley PN, Hedges LV. Accurate models vs. accurate estimates: A simulation study of Bayesian single-case experimental designs. Behavior Research Methods. 2021 Feb 11:1-7. link.springer.com/article/10.3758/s13428-020-01522-0
• Daza EJ. Causal analysis of self-tracked time series data using a counterfactual framework for N-of-1 trials. Methods of information in medicine. 2018 Feb;57(Suppl 1):e10. thieme-connect.de/products/ejournals/html/10.3414/ME16-02-0044
  • LaTeX pre-print (identical content) here
• Natesan P, Hedges LV. Bayesian unknown change-point models to investigate immediacy in single case designs. Psychological Methods. 2017 Dec;22(4):743. psycnet.apa.org/doiLanding?doi=10.1037%2Fmet0000134 (pdf)

Clinical Research + Clinical Trials + Clinical Practice

Links

• Unified Protocol Institute unifiedprotocol.com/
• Using connected sensor technologies to measure health at home npjdigitalmedcommunity.nature.com…

Publications

• Coravos A, Doerr M, Goldsack J, Manta C, Shervey M, Woods B, Wood WA. Modernizing and designing evaluation frameworks for connected sensor technologies in medicine. npj Digital Medicine. 2020 Mar 13;3(1):1-0. nature.com/articles/s41746-020-0237-3
• Marra C, Chen JL, Coravos A, Stern AD. Quantifying the use of connected digital products in clinical research. npj Digital Medicine. 2020 Apr 3;3(1):1-0. nature.com/articles/s41746-020-0259-x
• Selker HP, Cohen T, D’Agostino RB, Dere WH, Ghaemi SN, Honig PK, Kaitin KI, Kaplan HC, Kravitz RL, Larholt K, McElwee NE. A Useful and Sustainable Role for N‐of‐1 Trials in the Healthcare Ecosystem. Clinical Pharmacology & Therapeutics. 2022 Aug;112(2):224-32. ascpt.onlinelibrary.wiley.com/doi/10.1002/cpt.2425
• Selker HP, Dulko D, Greenblatt DJ, Palm M, Trinquart L. The use of N-of-1 trials to generate real-world evidence for optimal treatment of individuals and populations. Journal of Clinical and Translational Science. 2023 Jan;7(1):e203. ncbi.nlm.nih.gov/pmc/articles/PMC10565195/

Community

Links

• International Collaborative Network (ICN) for N-of-1 Clinical Trials and Single-Case Experimental Designs (SCEDs) nof1sced.org
• Open Humans openhumans.org
• Open mHealth openmhealth.org
• Quantified Self quantifiedself.com
• Sage Bionetworks sagebionetworks.org

Publications

• Chen C, Haddad D, Selsky J, Hoffman JE, Kravitz RL, Estrin DE, Sim I. Making sense of mobile health data: an open architecture to improve individual-and population-level health. Journal of medical Internet research. 2012;14(4):e112. jmir.org/2012/4/e112

Connectivity Map

Publications

• Beltz AM, Wright AG, Sprague BN, Molenaar PC. Bridging the nomothetic and idiographic approaches to the analysis of clinical data. Assessment. 2016 Aug;23(4):447-58. journals.sagepub.com/doi/abs/10.1177/1073191116648209

Deep Learning

Publications

• Matias I, Wac K. Dejà vu: Recurrent Neural Networks for health wearables data forecast. In2022 21st IEEE International Conference on Machine Learning and Applications (ICMLA) 2022 Dec 12 (pp. 1724-1731). IEEE. ieeexplore.ieee.org/abstract/document/10069171

Digital Phenotyping

Links

• Onnela Lab at Harvard T.H. Chan School of Public Health: Beiwe Research Platform hsph.harvard.edu/onnela-lab/beiwe-research-platform
• The AWARE Framework https://awareframework.com/
• The Reproducible Analysis Pipeline for Data Streams (RAPIDS) https://www.rapids.science/
• The Digital Biomarker Discovery Pipeline (DBDP) https://dbdp.org/
• The Learn, Assess, Manage, Prevent (LAMP) platform https://www.digitalpsych.org/lamp.html
• The Remote assessment of Disease And Relapse (RADAR) platform https://radar-base.org/
• The Effortless Assessment Research System (EARS) https://ksanahealth.com/ears

Publications

• Barnett I, Torous J, Staples P, Keshavan M, Onnela JP. Beyond smartphones and sensors: Choosing appropriate statistical methods for the analysis of longitudinal data. Journal of the American Medical Informatics Association. 2018 Dec;25(12):1669-74. academic.oup.com/jamia/article/25/12/1669/5110357
• Onnela JP, Rauch SL. Harnessing smartphone-based digital phenotyping to enhance behavioral and mental health. Neuropsychopharmacology. 2016 Jun;41(7):1691-6. nature.com/articles/npp20167

Dynamic Systems

Publications

• Molenaar PC, Valsiner J. How generalization works through the single case: A simple idiographic process analysis of an individual psychotherapy. YIS: Yearbook of idiographic science. 2009;1:23-38. researchgate.net/profile/Sergio_Salvatore/publication/235762368_….pdf#page=23
• Vieira R, McDonald S, Araújo-Soares V, Sniehotta FF, Henderson R. Dynamic modelling of n-of-1 data: powerful and flexible data analytics applied to individualised studies. Health Psychology Review. 2017 Jul 3;11(3):222-34. tandfonline.com/doi/full/10.1080/17437199.2017.1343680

Education

Publications

• Rose T. The end of average: How to succeed in a world that values sameness. Penguin UK; 2016 Jan 28. toddrose.com/endofaverage

Effect Size + Tau-U (from Kendall’s τ)

Publications

• Brossart DF, Laird VC, Armstrong TW. Interpreting Kendall’s Tau and Tau-U for single-case experimental designs. Cogent Psychology. 2018 Jan 1;5(1):1518687. cogentoa.com/article/10.1080/23311908.2018.1518687
• Chen LT, Wu PJ, Peng CY. Accounting for baseline trends in intervention studies: Methods, effect sizes, and software. Cogent Psychology. 2019 Jan 1;6(1):1679941. tandfonline.com/doi/full/10.1080/23311908.2019.1679941
• Manolov R, Solanas A. Comparing N= 1 effect size indices in presence of autocorrelation. Behavior modification. 2008 Nov;32(6):860-75. journals.sagepub.com/doi/abs/10.1177/0145445508318866
• Parker RI, Vannest K. An improved effect size for single-case research: Nonoverlap of all pairs. Behavior Therapy. 2009 Dec 1;40(4):357-67. sciencedirect.com/science/article/abs/pii/S0005789408000816
• Parker RI, Vannest KJ, Davis JL, Sauber SB. Combining nonoverlap and trend for single-case research: Tau-U. Behavior Therapy. 2011 Jun 1;42(2):284-99. sciencedirect.com/science/article/abs/pii/S0005789411000153
• Solanas A, Manolov R, Onghena P. Estimating slope and level change in N= 1 designs. Behavior Modification. 2010 May;34(3):195-218. journals.sagepub.com/doi/abs/10.1177/0145445510363306
• Tarlow KR. An improved rank correlation effect size statistic for single-case designs: Baseline corrected Tau. Behavior Modification. 2017 Jul;41(4):427-67. journals.sagepub.com/doi/abs/10.1177/0145445516676750
• Vannest KJ, Ninci J. Evaluating intervention effects in single‐case research designs. Journal of Counseling & Development. 2015 Oct;93(4):403-11. onlinelibrary.wiley.com/doi/abs/10.1002/jcad.12038

Functional Data Analysis

Publications

• Fok CC, Ramsay JO. Fitting curves with periodic and nonperiodic trends and their interactions with intensive longitudinal data. Models for intensive longitudinal data. 2006 Jan 19:109-23. oxford.universitypressscholarship.com/view/10.1093/acprof:oso/9780195173444.001.0001/acprof-9780195173444
• Li R, Root TL, Shiffman S. A local linear estimation procedure for functional multilevel modeling. Models for intensive longitudinal data. 2006 Jan 19:63-83. oxford.universitypressscholarship.com/view/10.1093/acprof:oso/9780195173444.001.0001/acprof-9780195173444
• Ramsay JO. Functional data analysis. Encyclopedia of Statistical Sciences 4 (2004). onlinelibrary.wiley.com/doi/abs/10.1002/0471667196.ess3138
• Ramsay JO. Functional data analysis—Theory. Wiley Online Library; 2014. onlinelibrary.wiley.com/doi/10.1002/9781118445112.stat00516.pub2/pdf
• Ramsay JO and Silverman BW. Applied functional data analysis: Methods and case studies. Springer, 2007. citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.468.2686&rep=rep1&type=pdf
• Tan X, Shiyko MP, Li R, Li Y, Dierker L. A time-varying effect model for intensive longitudinal data. Psychological methods. 2012 Mar;17(1):61. ncbi.nlm.nih.gov/pmc/articles/PMC3288551/

Generalization

Publications

• Kennedy MM. Generalizing from single case studies. Evaluation quarterly. 1979 Nov;3(4):661-78. journals.sagepub.com/doi/abs/10.1177/0193841x7900300409

Highly-Repeated Within-Person (HRWP)

Publications

• Whitsett DD, Shoda Y. An approach to test for individual differences in the effects of situations without using moderator variables. Journal of experimental social psychology. 2014 Jan 1;50:94-104. pmc.ncbi.nlm.nih.gov/articles/PMC3925438/
• Zayas V, Sridharan V, Lee RT, Shoda Y. Addressing two blind spots of commonly used experimental designs: The Highly‐Repeated Within‐Person approach. Social and Personality Psychology Compass. 2019 Sep;13(9):e12487. compass.onlinelibrary.wiley.com/doi/abs/10.1111/spc3.12487

Longitudinal Analysis

Publications

• Barnett I, Torous J, Staples P, Keshavan M, Onnela JP. Beyond smartphones and sensors: Choosing appropriate statistical methods for the analysis of longitudinal data. Journal of the American Medical Informatics Association. 2018 Dec;25(12):1669-74. academic.oup.com/jamia/article/25/12/1669/5110357
• Daza EJ. Person as Population: A Longitudinal View of Single-Subject Causal Inference for Analyzing Self-Tracked Health Data. arXiv preprint arXiv:1901.03423. 2019 Jan 10. arxiv.org/abs/1901.03423
• Lum K, Dunson DB, Johndrow J. Closer than they appear: A Bayesian perspective on individual-level heterogeneity in risk assessment. arXiv preprint arXiv:2102.01135. 2021 Feb 1. arxiv.org/abs/2102.01135
• Wang E, Cook D, Hyndman RJ. A new tidy data structure to support exploration and modeling of temporal data. Journal of Computational and Graphical Statistics. 2019 Dec 27:1-3. tandfonline.com/doi/abs/10.1080/10618600.2019.1695624

Machine Learning + Artificial Intelligence

Publications

• Daza EJ. Causal analysis of self-tracked time series data using a counterfactual framework for n-of-1 trials. Methods of Information in Medicine. 2018 Feb;57(01):e10-21. thieme-connect.de/products/ejournals/html/10.3414/ME16-02-0044
  • LaTeX version (identical content with cleanly formatted notation) here
• Daza EJ, Matias I, Schneider L. Model-Twin Randomization (MoTR) for Estimating One’s Own Recurring Individual Treatment Effect. Statistics in Medicine. 2024 Oct 1 under review. arxiv.org/abs/2208.00739 (2-min explainer video here)
• Malenica I, Bibaut A, van der Laan MJ. Adaptive Sequential Design for a Single Time-Series. arXiv preprint arXiv:2102.00102. 2021 Jan 29. arxiv.org/abs/2102.00102
• Matias I, Daza EJ, Wac K. What possibly affects nighttime heart rate? Conclusions from N-of-1 observational data. Digital Health. 2022 Aug 24. journals.sagepub.com/doi/10.1177/20552076221120725
• Nagesh N, Azimi I, Andriola T, Rahmani AM, Jain R. Towards Deep Personal Lifestyle Models Using Multimodal N-of-1 Data. InInternational Conference on Multimedia Modeling 2023 Jan 9 (pp. 589-600). Cham: Springer International Publishing. link.springer.com/chapter/10.1007/978-3-031-27077-2_46

Masked Visual Analysis

Links

• Single Case Design Masked Visual Analysis (SCD-MVA) App singlecasemva.app/

Publications

• Byun TM, Hitchcock ER, Ferron J. Masked visual analysis: Minimizing type I error in visually guided single-case design for communication disorders. Journal of Speech, Language, and Hearing Research. 2017 Jun 10;60(6):1455-66. [ncbi.nlm.nih.gov/pmc/articles/PMC5544408/(https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5544408/)]
• Ferron J, Jones PK. Tests for the visual analysis of response-guided multiple-baseline data. The Journal of Experimental Education. 2006 Oct 1;75(1):66-81. tandfonline.com/doi/abs/10.3200/JEXE.75.1.66-81
• Ferron JM, Joo SH, Levin JR. A Monte Carlo evaluation of masked visual analysis in response‐guided versus fixed‐criteria multiple‐baseline designs. Journal of applied behavior analysis. 2017 Oct;50(4):701-16. onlinelibrary.wiley.com/doi/abs/10.1002/jaba.410
• Ferron J, Rohrer LL, Levin JR. Randomization procedures for changing criterion designs. Behavior modification. 2019 May 12:0145445519847627. journals.sagepub.com/doi/abs/10.1177/0145445519847627
• Moeyaert M, Bursali S, Ferron JM. SCD‐MVA: A mobile application for conducting single‐case experimental design research during the pandemic. Human Behavior and Emerging Technologies. 2021 Jan;3(1):75-96. onlinelibrary.wiley.com/doi/full/10.1002/hbe2.223

Measurement Error

Publications

• Ferrari P, Friedenreich C, Matthews CE. The role of measurement error in estimating levels of physical activity. American journal of epidemiology. 2007 Oct 1;166(7):832-40. academic.oup.com/aje/article/166/7/832/94900

Missing Data

Publications

• Catellier DJ, Hannan PJ, Murray DM, Addy CL, Conway TL, Yang S, Rice JC. Imputation of missing data when measuring physical activity by accelerometry. Medicine and science in sports and exercise. 2005 Nov;37(11 Suppl):S555. ncbi.nlm.nih.gov/pmc/articles/PMC2435061
• Chen LT, Feng Y, Wu PJ, Peng CY. Dealing with missing data by EM in single-case studies. Behavior Research Methods. 2020 Feb;52(1):131-50. link.springer.com/article/10.3758/s13428-019-01210-8
• De TK, Michiels B, Tanious R, Onghena P. Handling missing data in randomization tests for single-case experiments: A simulation study. Behavior Research Methods. 2020 Jan 2:1-6. link.springer.com/article/10.3758/s13428-019-01320-3
• Fowler C, Cai X, Baker JT, Onnela JP, Valeri L. Testing unit root non-stationarity in the presence of missing data in univariate time series of mobile health studies. arXiv preprint arXiv:2210.04998. 2022 Oct 10. arxiv.org/abs/2210.04998
• Rowe DA, Mahar MT, Raedeke TD, Lore J. Measuring physical activity in children with pedometers: Reliability, reactivity, and replacement of missing data. Pediatric Exercise Science. 2004 Nov 1;16(4):343-54. researchgate.net/profile/David_Rowe/publication/251259986….pdf

Mobile Devices + Sensors + Wearables

Links

• Statistical Methods and Applications for Research in Technology (SMART) working group of the Department of Biostatistics in the Bloomberg School of Public Health at Johns Hopkins University (JHU) smart-stats.org
• Using connected sensor technologies to measure health at home npjdigitalmedcommunity.nature.com…
• Wearable and Implantable Technology (WIT) ciprianstats.org
• The AWARE Framework https://awareframework.com/
• The Reproducible Analysis Pipeline for Data Streams (RAPIDS) https://www.rapids.science/
• The Digital Biomarker Discovery Pipeline (DBDP) https://dbdp.org/
• The Learn, Assess, Manage, Prevent (LAMP) platform https://www.digitalpsych.org/lamp.html
• The Remote assessment of Disease And Relapse (RADAR) platform https://radar-base.org/
• The Effortless Assessment Research System (EARS) https://ksanahealth.com/ears

Publications

• Coravos A, Doerr M, Goldsack J, Manta C, Shervey M, Woods B, Wood WA. Modernizing and designing evaluation frameworks for connected sensor technologies in medicine. npj Digital Medicine. 2020 Mar 13;3(1):1-0. nature.com/articles/s41746-020-0237-3
• Daza EJ, Matias I, Schneider L. Model-Twin Randomization (MoTR) for Estimating One’s Own Recurring Individual Treatment Effect. Statistics in Medicine. 2024 Oct 1 under review. arxiv.org/abs/2208.00739 (2-min explainer video here)
• Matias I, Daza EJ, Wac K. What possibly affects nighttime heart rate? Conclusions from N-of-1 observational data. Digital Health. 2022 Aug 24. journals.sagepub.com/doi/10.1177/20552076221120725
• Nagesh N, Azimi I, Andriola T, Rahmani AM, Jain R. Towards Deep Personal Lifestyle Models Using Multimodal N-of-1 Data. InInternational Conference on Multimedia Modeling 2023 Jan 9 (pp. 589-600). Cham: Springer International Publishing. link.springer.com/chapter/10.1007/978-3-031-27077-2_46

Mobility

Links

• Stanford Mobilize Center mobilize.stanford.edu

Multiple Baseline Designs

Publications

• Bouwmeester S, and Jongerling J. Power of a randomization test in a single case multiple baseline AB design. PLOS ONE. 2020 Feb 6;15(2):e0228355. journals.plos.org/plosone/article?id=10.1371/journal.pone.0228355
• DeLoatche KJ. Parent-child interaction therapy as a treatment for ADHD in early childhood: A multiple baseline single-case design. University of South Florida; 2015. core.ac.uk/download/pdf/71953292.pdf
• Ferron J, Jones PK. Tests for the visual analysis of response-guided multiple-baseline data. The Journal of Experimental Education. 2006 Oct 1;75(1):66-81. tandfonline.com/doi/abs/10.3200/JEXE.75.1.66-81

N-of-1 Trials

Publications

• Araujo A, Julious S, Senn S. Understanding variation in sets of N-of-1 trials. PLoS One. 2016;11(12). ncbi.nlm.nih.gov/pmc/articles/PMC5131970
• Balandat M. New tools for econometric analysis of high-frequency time series data-application to demand-side management in electricity markets. University of California, Berkeley; 2016. search.proquest.com/openview/17ecbcf034eb521b90b63a6fe9c8a314/1?pq-origsite=gscholar&cbl=18750
• Blackston JW, Chapple AG, McGree JM, McDonald S, Nikles J. Comparison of Aggregated N-of-1 Trials with Parallel and Crossover Randomized Controlled Trials Using Simulation Studies. Healthcare 2019 Dec (Vol. 7, No. 4, p. 137). Multidisciplinary Digital Publishing Institute. mdpi.com/2227-9032/7/4/137
• Daza EJ. Causal analysis of self-tracked time series data using a counterfactual framework for N-of-1 trials. Methods of information in medicine. 2018 Feb;57(Suppl 1):e10. thieme-connect.de/products/ejournals/html/10.3414/ME16-02-0044
  • LaTeX pre-print (identical content) here
• Duan N, Kravitz RL, Schmid CH. Single-patient (n-of-1) trials: a pragmatic clinical decision methodology for patient-centered comparative effectiveness research. Journal of clinical epidemiology. 2013 Aug 1;66(8):S21-8. sciencedirect.com/science/article/pii/S089543561300156X
• Gabler NB, Duan N, Vohra S, Kravitz RL. N-of-1 trials in the medical literature: a systematic review. Medical care. 2011 Aug 1:761-8. jstor.org/stable/23053842
• Kravitz RL, Duan N, Niedzinski EJ, Hay MC, Subramanian SK, Weisner TS. What Ever Happened to N‐of‐1 Trials? Insiders’ Perspectives and a Look to the Future. The Milbank Quarterly. 2008 Dec;86(4):533-55. onlinelibrary.wiley.com/doi/full/10.1111/j.1468-0009.2008.00533.x
• Lillie EO, Patay B, Diamant J, Issell B, Topol EJ, Schork NJ. The n-of-1 clinical trial: the ultimate strategy for individualizing medicine?. Personalized medicine. 2011 Mar;8(2):161-73. ncbi.nlm.nih.gov/pmc/articles/PMC3118090
• Malenica I, Guo Y, Gan K, Konigorski S. Anytime-valid inference in N-of-1 trials. Machine Learning for Health (ML4H) 2023 Dec 4 (pp. 307-322). PMLR. proceedings.mlr.press/v225/malenica23a.html
• Nikles J, McDonald S (editors). Special Issue: N-of-1 Trials in Healthcare. Healthcare. 2019 Jul - 2020 Feb. 13 articles. mdpi.com/journal/healthcare/special_issues/N_of_1
• Schork NJ. Personalized medicine: time for one-person trials. Nature. 2015 Apr 30;520(7549):609-11. nature.com/news/personalized-medicine-time-for-one-person-trials-1.17411
• Selker HP, Cohen T, D’Agostino RB, Dere WH, Ghaemi SN, Honig PK, Kaitin KI, Kaplan HC, Kravitz RL, Larholt K, McElwee NE. A Useful and Sustainable Role for N‐of‐1 Trials in the Healthcare Ecosystem. Clinical Pharmacology & Therapeutics. 2022 Aug;112(2):224-32. ascpt.onlinelibrary.wiley.com/doi/10.1002/cpt.2425
• Selker HP, Dulko D, Greenblatt DJ, Palm M, Trinquart L. The use of N-of-1 trials to generate real-world evidence for optimal treatment of individuals and populations. Journal of Clinical and Translational Science. 2023 Jan;7(1):e203. ncbi.nlm.nih.gov/pmc/articles/PMC10565195/
• Senarathne SG, Overstall AM, McGree JM. Bayesian adaptive N‐of‐1 trials for estimating population and individual treatment effects. Statistics in Medicine. 2020 Dec 20;39(29):4499-518. onlinelibrary.wiley.com/doi/abs/10.1002/sim.8737
• Senn S. Suspended judgment n-of-1 trials. Controlled clinical trials. 1993 Feb 1;14(1):1-5. ftp://biostat.wisc.edu/pub/chappell/641/papers/paper20.pdf
• Senn S. Sample size considerations for n-of-1 trials. Statistical methods in medical research. 2019 Feb;28(2):372-83. journals.sagepub.com/doi/abs/10.1177/0962280217726801
• Senn S. The analysis of continuous data from n-of-1 trials using paired cycles: a simple tutorial. Trials. 2024 Feb 16;25(1):128. trialsjournal.biomedcentral.com/articles/10.1186/s13063-024-07964-7
• Shrestha S, Jain S. A Bayesian‐bandit adaptive design for N‐of‐1 clinical trials. Statistics in Medicine. 2021 Mar 30;40(7):1825-44. onlinelibrary.wiley.com/doi/abs/10.1002/sim.8873
• Tate RL, McDonald S, Perdices M, Togher L, Schultz R, Savage S. Rating the methodological quality of single-subject designs and n-of-1 trials: Introducing the Single-Case Experimental Design (SCED) Scale. Neuropsychological rehabilitation. 2008 Aug 1;18(4):385-401. tandfonline.com/doi/abs/10.1080/09602010802009201
• Vieira R, McDonald S, Araújo-Soares V, Sniehotta FF, Henderson R. Dynamic modelling of n-of-1 data: powerful and flexible data analytics applied to individualised studies. Health Psychology Review. 2017 Jul 3;11(3):222-34. tandfonline.com/doi/full/10.1080/17437199.2017.1343680
• Wang Y, Schork NJ. Power and Design Issues in Crossover-Based N-Of-1 Clinical Trials with Fixed Data Collection Periods. Healthcare 2019 Sep (Vol. 7, No. 3, p. 84). Multidisciplinary Digital Publishing Institute. mdpi.com/2227-9032/7/3/84

Other Time Series Approaches

Publications

• Dominguez AR, Yadav OH. A causal interactions indicator between two time series using extreme variations in the first eigenvalue of lagged correlation matrices. Data Science in Finance and Economics. 2024;4(3):422-45. papers.ssrn.com/sol3/papers.cfm?abstract_id=4841224
• Shojaie A, Fox EB. Granger causality: A review and recent advances. Annual Review of Statistics and Its Application. 2022 Mar 7;9(1):289-319. pmc.ncbi.nlm.nih.gov/articles/PMC10571505/

Overviews + Commentaries + Perspectives

Publications

• Augustine EF, Timothy WY, Finkel RS. N-of-1 Studies in an Era of Precision Medicine. JAMA. 2024. jamanetwork.com/journals/jama/article-abstract/2824089
• Barlow DH, Nock MK. Why can’t we be more idiographic in our research?. Perspectives on Psychological Science. 2009 Jan;4(1):19-21. journals.sagepub.com/doi/abs/10.1111/j.1745-6924.2009.01088.x
• Dallery J, Raiff BR. Optimizing behavioral health interventions with single-case designs: from development to dissemination. Translational behavioral medicine. 2014 Sep 1;4(3):290-303. academic.oup.com/tbm/article-abstract/4/3/290/4561509
• Davidson KW, Silverstein M, Cheung K, Paluch RA, Epstein LH. Experimental designs to optimize treatments for individuals: personalized N-of-1 trials. JAMA pediatrics. 2021 Apr 1;175(4):404-9. jamanetwork.com/journals/jamapediatrics/article-abstract/2776426
• Duan N, Kravitz RL, Schmid CH. Single-patient (n-of-1) trials: a pragmatic clinical decision methodology for patient-centered comparative effectiveness research. Journal of clinical epidemiology. 2013 Aug 1;66(8):S21-8. sciencedirect.com/science/article/pii/S089543561300156X
• Gouda MA, Buschhorn L, Schneeweiss A, Wahida A, Subbiah V. N-of-1 trials in cancer drug development. Cancer discovery. 2023 Jun 2;13(6):1301-9. aacrjournals.org/cancerdiscovery/article/13/6/1301/726949/N-of-1-Trials-in-Cancer-Drug-Development
• Kravitz RL, Duan N, Niedzinski EJ, Hay MC, Subramanian SK, Weisner TS. What Ever Happened to N‐of‐1 Trials? Insiders’ Perspectives and a Look to the Future. The Milbank Quarterly. 2008 Dec;86(4):533-55. onlinelibrary.wiley.com/doi/full/10.1111/j.1468-0009.2008.00533.x
• Lillie EO, Patay B, Diamant J, Issell B, Topol EJ, Schork NJ. The n-of-1 clinical trial: the ultimate strategy for individualizing medicine?. Personalized medicine. 2011 Mar;8(2):161-73. ncbi.nlm.nih.gov/pmc/articles/PMC3118090
• Nikles J, McDonald S (editors). Special Issue: N-of-1 Trials in Healthcare. Healthcare. 2019 Jul - 2020 Feb. 13 articles. mdpi.com/journal/healthcare/special_issues/N_of_1
• Ridenour TA, Pineo TZ, Molina MM, Lich KH. Toward rigorous idiographic research in prevention science: Comparison between three analytic strategies for testing preventive intervention in very small samples. Prevention Science. 2013 Jun 1;14(3):267-78. [ncbi.nlm.nih.gov/pmc/articles/PMC3782303/(https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3782303/)
• Schork NJ. Personalized medicine: time for one-person trials. Nature. 2015 Apr 30;520(7549):609-11. nature.com/news/personalized-medicine-time-for-one-person-trials-1.17411
• Selker HP, Cohen T, D’Agostino RB, Dere WH, Ghaemi SN, Honig PK, Kaitin KI, Kaplan HC, Kravitz RL, Larholt K, McElwee NE. A Useful and Sustainable Role for N‐of‐1 Trials in the Healthcare Ecosystem. Clinical Pharmacology & Therapeutics. 2022 Aug;112(2):224-32. ascpt.onlinelibrary.wiley.com/doi/10.1002/cpt.2425
• Selker HP, Dulko D, Greenblatt DJ, Palm M, Trinquart L. The use of N-of-1 trials to generate real-world evidence for optimal treatment of individuals and populations. Journal of Clinical and Translational Science. 2023 Jan;7(1):e203. ncbi.nlm.nih.gov/pmc/articles/PMC10565195/
• Senn S. Suspended judgment n-of-1 trials. Controlled clinical trials. 1993 Feb 1;14(1):1-5. ftp://biostat.wisc.edu/pub/chappell/641/papers/paper20.pdf
• Senn S. Statistical pitfalls of personalized medicine. Nature. 2018 Nov 27;563:619-621. nature.com/articles/d41586-018-07535-2
• Subbiah V. The next generation of evidence-based medicine. Nature medicine. 2023 Jan;29(1):49-58. www.nature.com/articles/s41591-022-02160-z
• US Food and Drug Administration. IND Submissions for Individualized Antisense Oligonucleotide Drug Products for Severely Debilitating or Life-Threatening Diseases: Chemistry, Manufacturing, and Controls Recommendations—Draft Guidance for Sponsor-Investigators. Center for Drug Evaluation and Research, US Department of Health and Human Services: Rockville, MD. 2021. fda.gov/regulatory-information/search-fda-guidance-documents/ind-submissions-individualized-antisense-oligonucleotide-drug-products-severely-debilitating-or-life
• Vlaeyen JW, Wicksell RK, Simons LE, Gentili C, De TK, Tate RL, Vohra S, Punja S, Linton SJ, Sniehotta FF, Onghena P. From Boulder to Stockholm in 70 Years: Single Case Experimental Designs in Clinical Research. The Psychological Record. 2020 Dec;70:659-70. link.springer.com/article/10.1007/s40732-020-00402-5

Quantitative Idiography

Publications

• Shoda Y, Wilson NL, Chen J, Gilmore AK, Smith RE. Cognitive‐affective processing system analysis of intra‐individual dynamics in collaborative therapeutic assessment: Translating basic theory and research into clinical applications. Journal of personality. 2013 Dec;81(6):554-68. onlinelibrary.wiley.com/doi/abs/10.1111/jopy.12015
• Shoda Y, Wilson NL, Whitsett DD, Lee-Dussud J, Zayas V. The person as a cognitive-affective processing system: Quantitative ideography as an integral component of cumulative science. psycnet.apa.org/record/2013-35883-021
• Brady LM, Fryberg SA, Shoda Y. Expanding the interpretive power of psychological science by attending to culture. Proceedings of the National Academy of Sciences. 2018 Nov 6;115(45):11406-13. pnas.org/doi/10.1073/pnas.1803526115

Randomization Tests

Publications

• Bouwmeester S, and Jongerling J. Power of a randomization test in a single case multiple baseline AB design. PLOS ONE. 2020 Feb 6;15(2):e0228355. journals.plos.org/plosone/article?id=10.1371/journal.pone.0228355
• De TK, Michiels B, Tanious R, Onghena P. Handling missing data in randomization tests for single-case experiments: A simulation study. Behavior Research Methods. 2020 Jan 2:1-6. link.springer.com/article/10.3758/s13428-019-01320-3
• Ferron J, Jones PK. Tests for the visual analysis of response-guided multiple-baseline data. The Journal of Experimental Education. 2006 Oct 1;75(1):66-81. tandfonline.com/doi/abs/10.3200/JEXE.75.1.66-81
• Ferron JM, Levin JR. Single-case permutation and randomization statistical tests: Present status, promising new developments. psycnet.apa.org/record/2013-42865-006
• Lall VF, Levin JR. An empirical investigation of the statistical properties of generalized single-case randomization tests. Journal of School Psychology. 2004 Jan 1;42(1):61-86. sciencedirect.com/science/article/pii/S0022440503001201
• MacKinnon DP, Smyth HL, Somers J, Ho E, Norget J, Miočević M. A randomization permutation test for single subject mediation. Evaluation & the health professions. 2022 Mar;45(1):54-65. https://journals.sagepub.com/doi/10.1177/01632787211070811

Repeated Measures + Individual Heterogeneity

Publications

• Lum K, Dunson DB, Johndrow J. Closer than they appear: A Bayesian perspective on individual-level heterogeneity in risk assessment. arXiv preprint arXiv:2102.01135. 2021 Feb 1. arxiv.org/abs/2102.01135
• Araujo A, Julious S, Senn S. Understanding variation in sets of N-of-1 trials. PLoS One. 2016;11(12). ncbi.nlm.nih.gov/pmc/articles/PMC5131970
• Shaffer JA, Kronish IM, Falzon L, Cheung YK, Davidson KW. N-of-1 randomized intervention trials in health psychology: a systematic review and methodology critique. Annals of Behavioral Medicine. 2018 Sep;52(9):731-42. academic.oup.com/abm/article/52/9/731/4837296

Sample Size + Statistical Power

Publications

• Blackston JW, Chapple AG, McGree JM, McDonald S, Nikles J. Comparison of Aggregated N-of-1 Trials with Parallel and Crossover Randomized Controlled Trials Using Simulation Studies. Healthcare 2019 Dec (Vol. 7, No. 4, p. 137). Multidisciplinary Digital Publishing Institute. mdpi.com/2227-9032/7/4/137
• Bouwmeester S, and Jongerling J. Power of a randomization test in a single case multiple baseline AB design. PLOS ONE. 2020 Feb 6;15(2):e0228355. journals.plos.org/plosone/article?id=10.1371/journal.pone.0228355
• Ferron J, Onghena P. The power of randomization tests for single-case phase designs. The Journal of Experimental Education. 1996 Apr 1;64(3):231-9. tandfonline.com/doi/abs/10.1080/00220973.1996.9943805
• Hedges, LV, Shadish, WR & Natesan Batley, P. Power analysis for single-case designs: Computations for (AB)k designs. Behav Res (2022). doi.org/10.3758/s13428-022-01971-9
• Percha B, Baskerville EB, Johnson M, Dudley JT, Zimmerman N. Designing Robust N-of-1 studies for precision medicine: Simulation study and design recommendations. Journal of Medical Internet Research. 2019;21(4):e12641. jmir.org/2019/4/e12641/
• Senn S. Sample size considerations for n-of-1 trials. Statistical methods in medical research. 2019 Feb;28(2):372-83. journals.sagepub.com/doi/abs/10.1177/0962280217726801
• Wang Y, Schork NJ. Power and Design Issues in Crossover-Based N-Of-1 Clinical Trials with Fixed Data Collection Periods. Healthcare 2019 Sep (Vol. 7, No. 3, p. 84). Multidisciplinary Digital Publishing Institute. mdpi.com/2227-9032/7/3/84

Self-Controlled Case Series

Publications

• Izem R, McCarter R. Randomized and non-randomized designs for causal inference with longitudinal data in rare disorders. Orphanet Journal of Rare Diseases. 2021 Dec;16:1-9. ojrd.biomedcentral.com/articles/10.1186/s13023-021-02124-5

Single-Case Experimental Designs (SCEDs) (SCDs) + Single-Subject Research/Designs

Links

• Single Case Research (SCR): web based calculators for SCR analysis singlecaseresearch.org

Publications

• Barlow DH, Nock MK. Why can’t we be more idiographic in our research?. Perspectives on Psychological Science. 2009 Jan;4(1):19-21. journals.sagepub.com/doi/abs/10.1111/j.1745-6924.2009.01088.x
• Batley PN, Hedges LV. Accurate models vs. accurate estimates: A simulation study of Bayesian single-case experimental designs. Behavior Research Methods. 2021 Feb 11:1-7. link.springer.com/article/10.3758/s13428-020-01522-0
• Bouwmeester S, and Jongerling J. Power of a randomization test in a single case multiple baseline AB design. PLOS ONE. 2020 Feb 6;15(2):e0228355. journals.plos.org/plosone/article?id=10.1371/journal.pone.0228355
• Brossart DF, Laird VC, Armstrong TW. Interpreting Kendall’s Tau and Tau-U for single-case experimental designs. Cogent Psychology. 2018 Jan 1;5(1):1518687. cogentoa.com/article/10.1080/23311908.2018.1518687
• Byun TM, Hitchcock ER, Ferron J. Masked visual analysis: Minimizing type I error in visually guided single-case design for communication disorders. Journal of Speech, Language, and Hearing Research. 2017 Jun 10;60(6):1455-66. [ncbi.nlm.nih.gov/pmc/articles/PMC5544408/(https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5544408/)]
• De TK, Michiels B, Tanious R, Onghena P. Handling missing data in randomization tests for single-case experiments: A simulation study. Behavior Research Methods. 2020 Jan 2:1-6. link.springer.com/article/10.3758/s13428-019-01320-3
• Declercq L, Cools W, Beretvas SN, Moeyaert M, Ferron JM, Van den Noortgate W. MultiSCED: A tool for (meta-) analyzing single-case experimental data with multilevel modeling. Behavior research methods. 2020 Feb;52(1):177-92. link.springer.com/article/10.3758/s13428-019-01216-2
• Declercq L, Jamshidi L, Fernández-Castilla B, Beretvas SN, Moeyaert M, Ferron JM, Van den Noortgate W. Analysis of single-case experimental count data using the linear mixed effects model: A simulation study. Behavior Research Methods. 2019 Dec;51(6):2477-97. link.springer.com/article/10.3758/s13428-018-1091-y
• Ferron J, Jones PK. Tests for the visual analysis of response-guided multiple-baseline data. The Journal of Experimental Education. 2006 Oct 1;75(1):66-81. tandfonline.com/doi/abs/10.3200/JEXE.75.1.66-81
• Ferron JM, Levin JR. Single-case permutation and randomization statistical tests: Present status, promising new developments. psycnet.apa.org/record/2013-42865-006
• Ferron J, Rohrer LL, Levin JR. Randomization procedures for changing criterion designs. Behavior modification. 2019 May 12:0145445519847627. journals.sagepub.com/doi/abs/10.1177/0145445519847627
• Hall GJ, Putzeys S, Kratochwill TR, Levin JR. Discovering Internal Validity Threats and Operational Concerns in Single-Case Experimental Designs Through Directed Acyclic Graphs. Educational Psychology Review. 2024 Dec;36(4):128. link.springer.com/article/10.1007/s10648-024-09962-2
• Hedges, LV, Shadish, WR & Natesan Batley, P. Power analysis for single-case designs: Computations for (AB)k designs. Behav Res (2022). doi.org/10.3758/s13428-022-01971-9
• Kennedy MM. Generalizing from single case studies. Evaluation quarterly. 1979 Nov;3(4):661-78. journals.sagepub.com/doi/abs/10.1177/0193841x7900300409
• Lall VF, Levin JR. An empirical investigation of the statistical properties of generalized single-case randomization tests. Journal of School Psychology. 2004 Jan 1;42(1):61-86. sciencedirect.com/science/article/pii/S0022440503001201
• Langenberg B, Wurpts IC, Geuke GG, Onghena P. Estimating and Testing Causal Mediation Effects in Single-Case Experimental Designs Using State-Space Modeling. Evaluation & the Health Professions. 2022:01632787211067533. journals.sagepub.com/doi/10.1177/01632787211067533
• Li H. Model selection of GLMMs in the analysis of count data in single-case studies: A Monte Carlo simulation. Behavior Research Methods. 2024 Jul 10:1-22. link.springer.com/article/10.3758/s13428-024-02464-7
• Li H, Luo W, Baek E. Multilevel modeling in single-case studies with zero-inflated and overdispersed count data. Behavior Research Methods. 2024 Feb 21:1-7. link.springer.com/article/10.3758/s13428-024-02359-7
• MacKinnon DP, Smyth HL, Somers J, Ho E, Norget J, Miočević M. A randomization permutation test for single subject mediation. Evaluation & the health professions. 2022 Mar;45(1):54-65. journals.sagepub.com/doi/10.1177/01632787211070811
• Manolov R, Gast DL, Perdices M, Evans JJ. Single-case experimental designs: Reflections on conduct and analysis. Neuropsychological rehabilitation. 2014 Jul 4;24(3-4):634-60. tandfonline.com/doi/abs/10.1080/09602011.2014.903199
• Manolov R, Rochat L. Analyzing data in single-case experimental designs: Objectives and available software options. Journal of Behavioral and Cognitive Therapy. 2024 Dec 1;34(4):100511. sciencedirect.com/science/article/pii/S2589979124000295
• Natesan P, Hedges LV. Bayesian unknown change-point models to investigate immediacy in single case designs. Psychological Methods. 2017 Dec;22(4):743. psycnet.apa.org/doiLanding?doi=10.1037%2Fmet0000134 (pdf)
• Natesan Batley P, Shukla Mehta S, Hitchcock JH. A Bayesian rate ratio effect size to quantify intervention effects for count data in single case experimental research. Behavioral Disorders. 2020 Jun 19:0198742920930704. journals.sagepub.com/doi/abs/10.1177/0198742920930704 (pdf)
• Smith JD. Single-case experimental designs: a systematic review of published research and current standards. Psychological methods. 2012 Dec;17(4):510. ncbi.nlm.nih.gov/pmc/articles/PMC3652808
• Tate RL, McDonald S, Perdices M, Togher L, Schultz R, Savage S. Rating the methodological quality of single-subject designs and n-of-1 trials: Introducing the Single-Case Experimental Design (SCED) Scale. Neuropsychological rehabilitation. 2008 Aug 1;18(4):385-401. tandfonline.com/doi/abs/10.1080/09602010802009201
• Van den Noortgate W, Onghena P. Combining single-case experimental data using hierarchical linear models. School Psychology Quarterly. 2003;18(3):325. psycnet.apa.org/record/2003-08719-005
• Vlaeyen JW, Wicksell RK, Simons LE, Gentili C, De TK, Tate RL, Vohra S, Punja S, Linton SJ, Sniehotta FF, Onghena P. From Boulder to Stockholm in 70 Years: Single Case Experimental Designs in Clinical Research. The Psychological Record. 2020 Dec;70:659-70. link.springer.com/article/10.1007/s40732-020-00402-5

Small Data

Links

• Quality of Life (QoL) Technologies Lab qualityoflifetechnologies.com
• Small Data Lab at Cornell Tech smalldata.io

Software Tools

Links

• CausalArima R package to estimate the causal effect of an intervention on a univariate time series using ARIMA models: github.com/FMenchetti/CausalArima
• hts: An R Package for Forecasting Hierarchical or Grouped Time Series cran.r-project.org/web/packages/hts/vignettes/hts.pdf
• List of single-case data analysis software tools osf.io/t6ws6/
• Single Case Design Masked Visual Analysis (SCD-MVA) App singlecasemva.app/
• Single Case Research (SCR): web based calculators for SCR analysis singlecaseresearch.org
• The AWARE Framework https://awareframework.com/
• The Reproducible Analysis Pipeline for Data Streams (RAPIDS) https://www.rapids.science/
• The Digital Biomarker Discovery Pipeline (DBDP) https://dbdp.org/
• The Learn, Assess, Manage, Prevent (LAMP) platform https://www.digitalpsych.org/lamp.html
• The Remote assessment of Disease And Relapse (RADAR) platform https://radar-base.org/
• The Effortless Assessment Research System (EARS) https://ksanahealth.com/ears
• StudyU Platform https://github.com/hpi-studyu/studyu

Publications

• Bulté I, Onghena P. The single-case data analysis package: Analysing single-case experiments with R software. Journal of Modern Applied Statistical Methods. 2013;12(2):28. digitalcommons.wayne.edu/cgi/viewcontent.cgi?article=1796&context=jmasm
• Declercq L, Cools W, Beretvas SN, Moeyaert M, Ferron JM, Van den Noortgate W. MultiSCED: A tool for (meta-) analyzing single-case experimental data with multilevel modeling. Behavior research methods. 2020 Feb;52(1):177-92. link.springer.com/article/10.3758/s13428-019-01216-2
• Konigorski S, Wernicke S, Slosarek T, Zenner AM, Strelow N, Ruether FD, Henschel F, Manaswini M, Pottbäcker F, Edelman JA, Owoyele B. StudyU: a platform for designing and conducting innovative digital N-of-1 trials. arXiv preprint arXiv:2012.14201. 2020 Dec 28. arxiv.org/abs/2012.14201
• Manolov R, Moeyaert M. How can single-case data be analyzed? Software resources, tutorial, and reflections on analysis. Behavior Modification. 2017 Mar;41(2):179-228. journals.sagepub.com/doi/abs/10.1177/0145445516664307
• Manolov R, Rochat L. Analyzing data in single-case experimental designs: Objectives and available software options. Journal of Behavioral and Cognitive Therapy. 2024 Dec 1;34(4):100511. sciencedirect.com/science/article/pii/S2589979124000295
• Moeyaert M, Bursali S, Ferron JM. SCD‐MVA: A mobile application for conducting single‐case experimental design research during the pandemic. Human Behavior and Emerging Technologies. 2021 Jan;3(1):75-96. onlinelibrary.wiley.com/doi/full/10.1002/hbe2.223
• Wang E, Cook D, Hyndman RJ. A new tidy data structure to support exploration and modeling of temporal data. Journal of Computational and Graphical Statistics. 2019 Dec 27:1-3. tandfonline.com/doi/abs/10.1080/10618600.2019.1695624

Special Issues + Collections

Publications

• Davidson K, Cheung K, Friel C, Suls J. Introducing Data Sciences to N-of-1 Designs, Statistics, Use-Cases, the Future, and the Moniker ‘N-of-1’Trial. Harvard Data Science Review. hdsr.mitpress.mit.edu/specialissue3 + hdsr.mitpress.mit.edu/pub/pv2y77y3/release/1?readingCollection=c31cf5ee
• Nikles J, McDonald S (editors). Special Issue: N-of-1 Trials in Healthcare. Healthcare. 2019 Jul - 2020 Feb. 13 articles. mdpi.com/journal/healthcare/special_issues/N_of_1
• Nikles J, Daza EJ, McDonald S, Hekler E, Schork NJ (editors). Research Topic: Creating Evidence from Real World Patient Digital Data. Frontiers in Computer Science (Digital Public Health), Frontiers in Psychiatry (Social Psychiatry and Psychiatric Rehabilitation, Public Mental Health), Frontiers in Psychology (Health Psychology, Psychology for Clinical Settings), Frontiers in Digital Health (Connected Health, Personalized Medicine, Health Informatics), Frontiers in Neurology (Neurorehabilitation), Frontiers in Public Health (Public Mental Health, Digital Public Health), Frontiers in Sociology (Public Mental Health). 2020 Feb - 2020 Oct. 13 articles. frontiersin.org/research-topics/10089

Sports + Athletic Performance

Publications

• Nakayama S, Trejo-Silva A, Gomez-Ruano MA, Aida H. Impact of a Ball Regulation Change on Game Performance and Shooting Play in Japanese U-15 Girls’ Handball. Perceptual and Motor Skills. 2024 Sep 19:00315125241274215. journals.sagepub.com/doi/abs/10.1177/00315125241274215
• Tweedy S, Dutia IM, Cairney J, Beckman E. Single case experimental design: a rigorous method for addressing inequity and enhancing precision within Para sport and exercise medicine research. British Journal of Sports Medicine. 2024 Sep 19. bjsm.bmj.com/content/early/2024/09/19/bjsports-2024-108587

Study Design, Analysis, Reporting

Links

• ICN Analysis Resources nof1andsced.wixsite.com/home/analysis
• Single Case Research (SCR): web based calculators for SCR analysis singlecaseresearch.org
• Using connected sensor technologies to measure health at home npjdigitalmedcommunity.nature.com…

Publications

• Araujo A, Julious S, Senn S. Understanding variation in sets of N-of-1 trials. PLoS One. 2016;11(12). ncbi.nlm.nih.gov/pmc/articles/PMC5131970
• Coravos A, Doerr M, Goldsack J, Manta C, Shervey M, Woods B, Wood WA. Modernizing and designing evaluation frameworks for connected sensor technologies in medicine. npj Digital Medicine. 2020 Mar 13;3(1):1-0. nature.com/articles/s41746-020-0237-3
• Ferron J, Jones PK. Tests for the visual analysis of response-guided multiple-baseline data. The Journal of Experimental Education. 2006 Oct 1;75(1):66-81. tandfonline.com/doi/abs/10.3200/JEXE.75.1.66-81
• Ferron J, Rohrer LL, Levin JR. Randomization procedures for changing criterion designs. Behavior modification. 2019 May 12:0145445519847627. journals.sagepub.com/doi/abs/10.1177/0145445519847627
• Franklin RD, Allison DB, Gorman BS, editors. Design and analysis of single-case research. Psychology Press; 2014 Jan 14. psycnet.apa.org/record/1997-97365-000
• Gorman BS, Allison DB. Statistical alternatives for single-case designs. Design and analysis of single-case research. 1996:159-214. taylorfrancis.com/books/e/9781315806402/chapters/10.4324/9781315806402-12
• Hott BL, Limberg D, Ohrt JH, Schmit MK. Reporting results of single‐case studies. Journal of Counseling & Development. 2015 Oct;93(4):412-7. onlinelibrary.wiley.com/doi/abs/10.1002/jcad.12039
• Huitema B. The analysis of covariance and alternatives: Statistical methods for experiments, quasi-experiments, and single-case studies. John Wiley & Sons; 2011 Oct 24. wiley.com/en-us/The+Analysis+of+Covariance+and+Alternatives…
• Kratochwill TR, Hitchcock JH, Horner RH, Levin JR, Odom SL, Rindskopf DM, Shadish WR. Single-case intervention research design standards. Remedial and Special Education. 2013 Jan;34(1):26-38. journals.sagepub.com/doi/abs/10.1177/0741932512452794
• Kratochwill TR, Hitchcock J, Horner RH, Levin JR, Odom SL, Rindskopf DM, Shadish WR. Single-case designs technical documentation. What works clearinghouse. 2010 Jun. eric.ed.gov/?id=ED510743
• Kravitz RL, Duan N, eds, and the DEcIDE Methods Center N-of-1 Guidance Panel (Duan N, Eslick I, Gabler NB, Kaplan HC, Kravitz RL, Larson EB, Pace WD, Schmid CH, Sim I, Vohra S). Design and Implementation of N-of-1 Trials: A User’s Guide. AHRQ Publication No. 13(14)-EHC122-EF. Rockville, MD: Agency for Healthcare Research and Quality; February 2014. effectivehealthcare.ahrq.gov/products/n-1-trials/research-2014-5
• Logan LR, Hickman RR, Harris SR, Heriza CB. Single‐subject research design: recommendations for levels of evidence and quality rating. Developmental medicine & child neurology. 2008 Feb;50(2):99-103. onlinelibrary.wiley.com/doi/abs/10.1111/j.1469-8749.2007.02005.x
• Manolov R, Moeyaert M. Recommendations for choosing single-case data analytical techniques. Behavior Therapy. 2017 Jan 1;48(1):97-114. sciencedirect.com/science/article/abs/pii/S0005789416300284
• Manolov R, Onghena P. Analyzing data from single-case alternating treatments designs. Psychological Methods. 2018 Sep;23(3):480. psycnet.apa.org/doiLanding?doi=10.1037%2Fmet0000133
• McDonald S, Vieira R, Johnston DW. Analysing N-of-1 observational data in health psychology and behavioural medicine: A 10-step SPSS tutorial for beginners. Health Psychology and Behavioral Medicine. 2020 Jan 1;8(1):32-54. tandfonline.com/doi/full/10.1080/21642850.2019.1711096
• Naughton F, Johnston D. A starter kit for undertaking n-of-1 trials. The European Health Psychologist. 2014;16(5):196-205. ueaeprints.uea.ac.uk/id/eprint/61949
• Nikles J and Mitchell G, eds. The essential guide to N-of-1 trials in health. New York, NY, USA:: Springer, 2015. link.springer.com/book/10.1007%2F978-94-017-7200-6
• Percha B, Baskerville EB, Johnson M, Dudley JT, Zimmerman N. Designing Robust N-of-1 studies for precision medicine: Simulation study and design recommendations. Journal of Medical Internet Research. 2019;21(4):e12641. jmir.org/2019/4/e12641/
• Ridenour TA, Chen SH, Liu HY, Bobashev GV, Hill K, Cooper R. The clinical trials mosaic: toward a range of clinical trials designs to optimize evidence-based treatment. Journal for Person-Oriented Research. 2017;3(1):28-48. [person-research.org/journal/files/3_1/filer/5.pdf(https://www.person-research.org/journal/files/3\_1/filer/5.pdf)
• Senn, S. Making it personal: N-of-1 trials, allowing for individuality but not overdoing it. nQuery Sample Size Software Team. 2017 Jan 11. blog.statsols.com/making-it-personal-n-of-1-trials-allowing-for-individuality-but-not-overdoing-it
• Senarathne SG, Overstall AM, McGree JM. Bayesian adaptive N‐of‐1 trials for estimating population and individual treatment effects. Statistics in Medicine. 2020 Dec 20;39(29):4499-518. onlinelibrary.wiley.com/doi/abs/10.1002/sim.8737
• Smith JD. Single-case experimental designs: a systematic review of published research and current standards. Psychological methods. 2012 Dec;17(4):510. ncbi.nlm.nih.gov/pmc/articles/PMC3652808
• Tate RL, McDonald S, Perdices M, Togher L, Schultz R, Savage S. Rating the methodological quality of single-subject designs and n-of-1 trials: Introducing the Single-Case Experimental Design (SCED) Scale. Neuropsychological rehabilitation. 2008 Aug 1;18(4):385-401. tandfonline.com/doi/abs/10.1080/09602010802009201
• Tate RL, Perdices M, Rosenkoetter U, Shadish W, Vohra S, Barlow DH, Horner R, Kazdin A, Kratochwill T, McDonald S, Sampson M, Shamseer L, Togher L, Albin R, Backman C, Douglas J, Evans JJ, Gast D, Manolov R, Mitchell G, Nickels L, Nikles J, Ownsworth T, Rose M, Schmid CH, Wilson B. The single-case reporting guideline in behavioural interventions (SCRIBE) 2016 statement. Physical Therapy. 2016 Jul 1;96(7):e1-0. academic.oup.com/ptj/article/96/7/e1/2864911
• Vohra S, Shamseer L, Sampson M, Bukutu C, Schmid CH, Tate R, Nikles J, Zucker DR, Kravitz R, Guyatt G, Altman DG. CONSORT extension for reporting N-of-1 trials (CENT) 2015 Statement. bmj. 2015 May 14;350:h1738. bmj.com/content/bmj/350/bmj.h1738.full.pdf
• Wang Y, Schork NJ. Power and Design Issues in Crossover-Based N-Of-1 Clinical Trials with Fixed Data Collection Periods. Healthcare 2019 Sep (Vol. 7, No. 3, p. 84). Multidisciplinary Digital Publishing Institute. mdpi.com/2227-9032/7/3/84

Switchback Experiments

Publications

• Bojinov I, Simchi-Levi D, Zhao J. Design and analysis of switchback experiments. Management Science. 2023 Jul;69(7):3759-77. pubsonline.informs.org/doi/abs/10.1287/mnsc.2022.4583

Systematic Reviews

Publications

• Gabler NB, Duan N, Vohra S, Kravitz RL. N-of-1 trials in the medical literature: a systematic review. Medical care. 2011 Aug 1:761-8. jstor.org/stable/23053842
• Müller AR, Brands MM, van de Ven PM, Roes KC, Cornel MC, van Karnebeek CD, Wijburg FA, Daams JG, Boot E, van Eeghen AM. Systematic review of N-of-1 studies in rare genetic neurodevelopmental disorders: the power of 1. Neurology. 2021 Mar 16;96(11):529-40. neurology.org/doi/full/10.1212/WNL.0000000000011597
• Shaffer JA, Kronish IM, Falzon L, Cheung YK, Davidson KW. N-of-1 randomized intervention trials in health psychology: a systematic review and methodology critique. Annals of Behavioral Medicine. 2018 Sep;52(9):731-42. academic.oup.com/abm/article/52/9/731/4837296
• Smith JD. Single-case experimental designs: a systematic review of published research and current standards. Psychological methods. 2012 Dec;17(4):510. ncbi.nlm.nih.gov/pmc/articles/PMC3652808

Time Series

Publications

• Beltz AM, Wright AG, Sprague BN, Molenaar PC. Bridging the nomothetic and idiographic approaches to the analysis of clinical data. Assessment. 2016 Aug;23(4):447-58. journals.sagepub.com/doi/abs/10.1177/1073191116648209
• Bojinov I, Shephard N. Time series experiments and causal estimands: exact randomization tests and trading. Journal of the American Statistical Association. 2019 Oct 2;114(528):1665-82. tandfonline.com/doi/abs/10.1080/01621459.2018.1527225
• Bojinov I, Simchi-Levi D, Zhao J. Design and analysis of switchback experiments. Management Science. 2023 Jul;69(7):3759-77. pubsonline.informs.org/doi/abs/10.1287/mnsc.2022.4583
• Cai X, Zeng L, Fowler C, Dixon L, Ongur D, Baker JT, Onnela JP, Valeri L. Causal estimands and identification of time-varying effects in non-stationary time series from N-of-1 mobile device data. arXiv preprint arXiv:2407.17666. 2024 Jul 24. arxiv.org/abs/2407.17666
• Daza EJ. Person as Population: A Longitudinal View of Single-Subject Causal Inference for Analyzing Self-Tracked Health Data. arXiv preprint arXiv:1901.03423. 2019 Jan 10. arxiv.org/abs/1901.03423
• Daza EJ. Causal analysis of self-tracked time series data using a counterfactual framework for n-of-1 trials. Methods of Information in Medicine. 2018 Feb;57(01):e10-21. thieme-connect.de/products/ejournals/html/10.3414/ME16-02-0044
  • LaTeX version (identical content with cleanly formatted notation) here
• Daza EJ, Matias I, Schneider L. Model-Twin Randomization (MoTR) for Estimating One’s Own Recurring Individual Treatment Effect. Statistics in Medicine. 2024 Oct 1 under review. arxiv.org/abs/2208.00739 (2-min explainer video here)
• Eichler M. Causal inference in time series analysis. Causality: Statistical perspectives and applications. 2012 Jul 13:327-54. onlinelibrary.wiley.com/doi/book/10.1002/9781119945710
• Fowler C, Cai X, Baker JT, Onnela JP, Valeri L. Testing unit root non-stationarity in the presence of missing data in univariate time series of mobile health studies. arXiv preprint arXiv:2210.04998. 2022 Oct 10. arxiv.org/abs/2210.04998
• Goldstein H, Healy MJ, Rasbash J. Multilevel time series models with applications to repeated measures data. Statistics in medicine. 1994 Aug 30;13(16):1643-55. onlinelibrary.wiley.com/doi/abs/10.1002/sim.4780131605
• Golino H, Christensen AP, Nesselroade JR. Towards a psychology of individuals: the ergodicity information index and a bottom-up approach for finding generalizations 2022. doi:10.31234/osf.io/th6rm. psyarxiv.com/th6rm
• Hyndman RJ, Athanasopoulos G, Shang HL. hts: An R Package for Forecasting Hierarchical or Grouped Time Series. R Package 2015. cran.r-project.org/web/packages/hts/vignettes/hts.pdf
• Krajewski T, Hudgens M. The augmented synthetic control method in public health and biomedical research. Statistical Methods in Medical Research. 2024 Feb 6:09622802231224638. journals.sagepub.com/doi/full/10.1177/09622802231224638
• Linden A. A matching framework to improve causal inference in interrupted time‐series analysis. Journal of Evaluation in Clinical Practice. 2018 Apr;24(2):408-15. onlinelibrary.wiley.com/doi/abs/10.1111/jep.12874
• Malenica I, Bibaut A, van der Laan MJ. Adaptive Sequential Design for a Single Time-Series. arXiv preprint arXiv:2102.00102. 2021 Jan 29. arxiv.org/abs/2102.00102
• Menchetti F, Cipollini F, Mealli F. Combining counterfactual outcomes and ARIMA models for policy evaluation. The Econometrics Journal. 2023 Jan;26(1):1-24. academic.oup.com/ectj/article/26/1/1/6713620
  • R package: github.com/FMenchetti/CausalArima
• Molenaar PC, Valsiner J. How generalization works through the single case: A simple idiographic process analysis of an individual psychotherapy. YIS: Yearbook of idiographic science. 2009;1:23-38. researchgate.net/profile/Sergio_Salvatore/publication/235762368_….pdf#page=23
• Neto EC, Bot BM, Perumal T, Omberg L, Guinney J, Kellen M, Klein A, Friend SH, Trister AD. Personalized hypothesis tests for detecting medication response in Parkinson disease patients using iPhone Sensor data. InBiocomputing 2016: Proceedings of the Pacific Symposium 2016 (pp. 273-284). ncbi.nlm.nih.gov/pubmed/26776193
• Neto EC, Prentice RL, Bot BM, Kellen M, Friend SH, Trister AD, Omberg L, Mangravite L. Towards personalized causal inference of medication response in mobile health: an instrumental variable approach for randomized trials with imperfect compliance. arXiv preprint arXiv:1604.01055. 2016 Apr 4. arxiv.org/abs/1604.01055
• Runge J, Gerhardus A, Varando G, Eyring V, Camps-Valls G. Causal inference for time series. Nature Reviews Earth & Environment. 2023 Jul;4(7):487-505. nature.com/articles/s43017-023-00431-y
• van der Laan MJ, Malenica I. Robust Estimation of Data-Dependent Causal Effects based on Observing a Single Time-Series. arXiv preprint arXiv:1809.00734. 2018 Sep 3. arxiv.org/abs/1809.00734
• Vieira R, McDonald S, Araújo-Soares V, Sniehotta FF, Henderson R. Dynamic modelling of n-of-1 data: powerful and flexible data analytics applied to individualised studies. Health Psychology Review. 2017 Jul 3;11(3):222-34. tandfonline.com/doi/full/10.1080/17437199.2017.1343680
• Wang E, Cook D, Hyndman RJ. A new tidy data structure to support exploration and modeling of temporal data. Journal of Computational and Graphical Statistics. 2019 Dec 27:1-3. tandfonline.com/doi/abs/10.1080/10618600.2019.1695624
• Wu X, Weinberger KR, Wellenius GA, Dominici F, Braun D. Assessing the causal effects of a stochastic intervention in time series data: Are heat alerts effective in preventing deaths and hospitalizations?. arXiv preprint arXiv:2102.10478. 2021 Feb 20. arxiv.org/abs/2102.10478

Tutorials

Links

• Jhangiani RS, Chiang IA, Price PC. Research methods in psychology-2nd Canadian Edition (Chapter 10: Single-Subject Research). BC Campus; 2015. opentextbc.ca/researchmethods/chapter/single-subject-research-designs/
• Manolov R, Moeyaert M. How can single-case data be analyzed? Software resources, tutorial, and reflections on analysis. Behavior Modification. 2017 Mar;41(2):179-228. journals.sagepub.com/doi/abs/10.1177/0145445516664307
• McDonald S, Vieira R, Johnston DW. Analysing N-of-1 observational data in health psychology and behavioural medicine: A 10-step SPSS tutorial for beginners. Health Psychology and Behavioral Medicine. 2020 Jan 1;8(1):32-54. tandfonline.com/doi/full/10.1080/21642850.2019.1711096
• Senn S. The analysis of continuous data from n-of-1 trials using paired cycles: a simple tutorial. Trials. 2024 Feb 16;25(1):128. trialsjournal.biomedcentral.com/articles/10.1186/s13063-024-07964-7
• University of Connecticut: Neag School of Education: Educational Research Basics by Del Siegle: Single Subject Research researchbasics.education.uconn.edu/single-subject-research/

Publications

• Jhangiani RS, Chiang IA, Price PC. Research methods in psychology-2nd Canadian Edition (Chapter 10: Single-Subject Research). BC Campus; 2015. opentextbc.ca/researchmethods/chapter/single-subject-research-designs/

Variable and Model Selection

Publications

• Li H. Model selection of GLMMs in the analysis of count data in single-case studies: A Monte Carlo simulation. Behavior Research Methods. 2024 Jul 10:1-22. link.springer.com/article/10.3758/s13428-024-02464-7
• Pascual C, Diaz K, Jain S. Multivariate variable selection in N-of-1 observational studies via additive Bayesian networks. Plos one. 2024 Aug 26;19(8):e0305225. journals.plos.org/plosone/article?id=10.1371/journal.pone.0305225

Visualization

Publications

• Byun TM, Hitchcock ER, Ferron J. Masked visual analysis: Minimizing type I error in visually guided single-case design for communication disorders. Journal of Speech, Language, and Hearing Research. 2017 Jun 10;60(6):1455-66. [ncbi.nlm.nih.gov/pmc/articles/PMC5544408/(https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5544408/)]
• Dart EH, Radley KC. Toward a standard assembly of linear graphs. School Psychology Quarterly. 2018 Sep;33(3):350. psycnet.apa.org/record/2018-32195-001
• Daza EJ, Wac K, Oppezzo M. Effects of Sleep Deprivation on Blood Glucose, Food Cravings, and Affect in a Non-Diabetic: An N-of-1 Randomized Pilot Study. Healthcare 2020 Mar (Vol. 8, No. 1, p. 6). Multidisciplinary Digital Publishing Institute. mdpi.com/2227-9032/8/1/6
• Ferron J, Jones PK. Tests for the visual analysis of response-guided multiple-baseline data. The Journal of Experimental Education. 2006 Oct 1;75(1):66-81. tandfonline.com/doi/abs/10.3200/JEXE.75.1.66-81
• Ferron JM, Joo SH, Levin JR. A Monte Carlo evaluation of masked visual analysis in response‐guided versus fixed‐criteria multiple‐baseline designs. Journal of applied behavior analysis. 2017 Oct;50(4):701-16. onlinelibrary.wiley.com/doi/abs/10.1002/jaba.410
• Ferron J, Rohrer LL, Levin JR. Randomization procedures for changing criterion designs. Behavior modification. 2019 May 12:0145445519847627. journals.sagepub.com/doi/abs/10.1177/0145445519847627
• Lane JD, Gast DL. Visual analysis in single case experimental design studies: Brief review and guidelines. Neuropsychological rehabilitation. 2014 Jul 4;24(3-4):445-63. tandfonline.com/doi/abs/10.1080/09602011.2013.815636
• Moeyaert M, Bursali S, Ferron JM. SCD‐MVA: A mobile application for conducting single‐case experimental design research during the pandemic. Human Behavior and Emerging Technologies. 2021 Jan;3(1):75-96. onlinelibrary.wiley.com/doi/full/10.1002/hbe2.223
• Radley KC, Dart EH. Graphing data and visual analysis. 2019. psycnet.apa.org/record/2019-15833-005
• Wang E, Cook D, Hyndman RJ. A new tidy data structure to support exploration and modeling of temporal data. Journal of Computational and Graphical Statistics. 2019 Dec 27:1-3. tandfonline.com/doi/abs/10.1080/10618600.2019.1695624