Impact of complex, partially nested clustering in a three-arm individually randomized group treatment trial: A case study with the wHOPE trial

1. Murray, DM, Taljaard, M, Turner, EL, et al. Essential ingredients and innovations in the design and analysis of group-randomized trials. Annu Rev Publ Health 2020; 41: 1–19.
Google Scholar | Crossref | Medline2. Pals, SL, Murray, DM, Alfano, CM, et al. Individually randomized group treatment trials: a critical appraisal of frequently used design and analytic approaches. Am J Publ Health 2008; 98(8): 1418–1424.
Google Scholar | Crossref | Medline3. Lee, KJ, Thompson, SG. Clustering by health professional in individually randomised trials. BMJ 2005; 330(7483): 142–144.
Google Scholar | Crossref | Medline4. Roberts, C, Roberts, SA. Design and analysis of clinical trials with clustering effects due to treatment. Clin Trials 2005; 2(2): 152–162.
Google Scholar | SAGE Journals | ISI5. Seal, KH, Becker, WC, Murphy, JL, et al. Whole Health Options and Pain Education (wHOPE): a pragmatic trial comparing whole health team versus primary care group education to promote non-pharmacological strategies to improve pain, functioning and quality of life in veterans—rationale, methods and implementation. Pain Med 2020; 21(Suppl. 2): S91–S99.
Google Scholar | Medline6. Roberts, C, Walwyn, R. Design and analysis of non-pharmacological treatment trials with multiple therapists per patient. Stat Med 2013; 32(1): 81–98.
Google Scholar | Crossref | Medline7. Walwyn, R, Roberts, C. Therapist variation within randomised trials of psychotherapy: implications for precision, internal and external validity. Stat Methods Med Res 2010; 19(3): 291–315.
Google Scholar | SAGE Journals | ISI8. Browne, WJ, Goldstein, H, Rasbash, J. Multiple membership multiple classification (MMMC) models. Stat Model 2001; 1(2): 103–124.
Google Scholar | SAGE Journals | ISI9. Sterba, SK. Partially nested designs in psychotherapy trials: a review of modeling developments. Psychother Res 2017; 27(4): 425–436.
Google Scholar | Crossref | Medline10. Moerbeek, M, Wong, WK. Sample size formulae for trials comparing group and individual treatments in a multilevel model. Stat Med 2008; 27(15): 2850–2864.
Google Scholar | Crossref | Medline11. Bauer, DJ, Sterba, SK, Hallfors, DD. Evaluating group-based interventions when control participants are ungrouped. Multivar Behav Res 2008; 43(2): 210–236.
Google Scholar | Crossref | Medline12. Esserman, D, Zhao, Y, Tang, Y, et al. Sample size estimation in educational intervention trials with subgroup heterogeneity in only one arm. Stat Med 2013; 32(12): 2140–2154.
Google Scholar | Crossref | Medline13. Seal, KH, Borsari, B, Tighe, J, et al. Optimizing pain treatment interventions (OPTI): a pilot randomized controlled trial of collaborative care to improve chronic pain management and opioid safety—rationale, methods, and lessons learned. Contemp Clin Trials 2019; 77: 76–85.
Google Scholar | Crossref | Medline14. Tan, G, Jensen, MP, Thornby, JI, et al. Validation of the Brief Pain Inventory for chronic nonmalignant pain. J Pain 2004; 5(2): 133–137.
Google Scholar | Crossref | Medline | ISI15. Eldridge, SM, Ashby, D, Feder, GS, et al. Lessons for cluster randomized trials in the twenty-first century: a systematic review of trials in primary care. Clin Trials 2004; 1(1): 80–90.
Google Scholar | SAGE Journals16. Spiegelhalter, DJ. Bayesian methods for cluster randomized trials with continuous responses. Stat Med 2001; 20(3): 435–452.
Google Scholar | Crossref | Medline | ISI17. Rasbash, J, Browne, W, Goldstein, H. A user’s guide to MLwiN, v2.33, 2014, http://www.bristol.ac.uk/cmm/media/software/mlwin/downloads/manuals/2-32/manual-web.pdf
Google Scholar18. Lake, S, Kammann, E, Klar, N, et al. Sample size re-estimation in cluster randomization trials. Stat Med 2002; 21(10): 1337–1350.
Google Scholar | Crossref | Medline | ISI19. van Schie, S, Moerbeek, M. Re-estimating sample size in cluster randomised trials with active recruitment within clusters. Stat Med 2014; 33(19): 3253–3268.
Google Scholar | Crossref | Medline20. Innocenti, F, Candel, MJ, Tan, FE, et al. Optimal two-stage sampling for mean estimation in multilevel populations when cluster size is informative. Stat Methods Med Res 2021; 30(2): 357–375.
Google Scholar | SAGE Journals | ISI21. Korendijk, EJ, Moerbeek, M, Maas, CJ. The robustness of designs for trials with nested data against incorrect initial intracluster correlation coefficient estimates. J Educ Behav Stat 2010; 35(5): 566–585.
Google Scholar | SAGE Journals22. Moerbeek, M, Teerenstra, S. Power analysis of trials with multilevel data. Boca Raton, FL: CRC Press, 2015.
Google Scholar | Crossref23. Baldwin, SA, Fellingham, GW. Bayesian methods for the analysis of small sample multilevel data with a complex variance structure. Psychol Methods 2013; 18(2): 151–164.
Google Scholar | Crossref | Medline24. Turner, RM, Omar, RZ, Thompson, SG. Constructing intervals for the intracluster correlation coefficient using Bayesian modelling, and application in cluster randomized trials. Stat Med 2006; 25(9): 1443–1456.
Google Scholar | Crossref | Medline25. Turner, RM, Thompson, SG, Spiegelhalter, DJ. Prior distributions for the intracluster correlation coefficient, based on multiple previous estimates, and their application in cluster randomized trials. Clin Trials 2005; 2(2): 108–118.
Google Scholar | SAGE Journals | ISI

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