Required sample size to detect mediation in 3-level implementation studies

Eccles MP, Mittman BS. Welcome to implementation science. Implement Sci. 2006;1:1. https://doi.org/10.1186/1748-5908-1-1.

Article  PubMed Central  Google Scholar 

Nilsen P. Making sense of implementation theories, models and frameworks. Implement Sci. 2015;10:53. https://doi.org/10.1186/s13012-015-0242-0.

Article  PubMed  PubMed Central  Google Scholar 

Williams NJ, Beidas RS. Annual research review: the state of implementation science in child psychology and psychiatry: a review and suggestions to advance the field. J Child Psychol Psychiatry. 2019;60:430–50. https://doi.org/10.1111/jcpp.12960.

Article  PubMed  Google Scholar 

Lewis CC, Boyd MR, Walsh-Bailey C, Lyon AR, Beidas R, Mittman B, et al. A systematic review of empirical studies examining mechanisms of implementation in health. Implement Sci. 2020;15:21. https://doi.org/10.1186/s13012-020-00983-3.

Article  PubMed  PubMed Central  Google Scholar 

Williams NJ. Multilevel mechanisms of implementation strategies in mental health: integrating theory, research, and practice. Admin Pol Ment Health. 2016;43:783–98. https://doi.org/10.1007/s10488-015-0693-2.

Article  Google Scholar 

Baron RM, Kenny DA. The moderator–mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. J Pers Soc Psychol. 1986;51:1173–82. https://doi.org/10.1037/0022-3514.51.6.1173.

CAS  Article  PubMed  Google Scholar 

MacKinnon DP. Introduction to statistical mediation analysis: Routledge; 2007.

Google Scholar 

Hayes AF. Introduction to mediation, moderation, and conditional process analysis: a regression-based approach. 1st ed: Guilford Publications; 2017.

Google Scholar 

Preacher KJ. Advances in mediation analysis: a survey and synthesis of new developments. Annu Rev Psychol. 2015;66:825–52. https://doi.org/10.1146/annurev-psych-010814-015258.

Article  PubMed  Google Scholar 

VanderWeele T. Explanation in causal inference: methods for mediation and interaction: Oxford University Press; 2015.

Google Scholar 

Insel TR. The NIMH experimental medicine initiative. World Psychiatry. 2015;14:151.

Article  Google Scholar 

Lewandowski KE, Ongur D, Keshavan MS. Development of novel behavioral interventions in an experimental therapeutics world: challenges, and directions for the future. Schizophr Res. 2018;192:6–8.

Article  Google Scholar 

Nielsen L, Riddle M, King JW, Aklin WM, Chen W, Clark D, et al. The NIH science of behavior change program: transforming the science through a focus on mechanisms of change. Behav Res Ther. 2018;101:3–11.

Article  Google Scholar 

Lewis CC, Powell BJ, Brewer SK, Nguyen AM, Schriger SH, Vejnoska SF, et al. Advancing mechanisms of implementation to accelerate sustainable evidence-based practice integration: protocol for generating a research agenda. BMJ Open. 2021;11(10):e053474.

Article  Google Scholar 

Weiner BJ, Lewis MA, Clauser SB, Stitzenberg KB. In search of synergy: strategies for combining interventions at multiple levels. J Natl Cancer Inst Monogr. 2012;44:34–41.

Article  Google Scholar 

Grol RP, Bosch MC, Hulscher ME, Eccles MP, Wensing M. Planning and studying improvement in patient care: the use of theoretical perspectives. Milbank Quart. 2007;85(1):93–138.

Article  Google Scholar 

Wolfenden L, Foy R, Presseau J, Grimshaw JM, Ivers NM, Powell BJ, et al. Designing and undertaking randomised implementation trials: guide for researchers. BMJ. 2021;372:m3721. https://doi.org/10.1136/bmj.m3721.

Article  PubMed  PubMed Central  Google Scholar 

McIntyre SA, Francis JJ, Gould NJ, Lorencatto F. The use of theory in process evaluations conducted alongside randomized trials of implementation interventions: a systematic review. Transl Behav Med. 2020;10:168–78.

PubMed  Google Scholar 

Beidas RS, Ahmedani B, Linn KA, et al. Study protocol for a type III hybrid effectiveness-implementation trial of strategies to implement firearm safety promotion as a universal suicide prevention strategy in pediatric primary care. Implement Sci. 2021;16(89). https://doi.org/10.1186/s13012-021-01154-8.

Kohrt BA, Turner EL, Gurung D, et al. Implementation strategy in collaboration with people with lived experience of mental illness to reduce stigma among primary care providers in Nepal (RESHAPE): protocol for a type 3 hybrid implementation effectiveness cluster randomized controlled trial. Implement Sci. 2022;17(39). https://doi.org/10.1186/s13012-022-01202-x.

Cumbe VFJ, Muanido AG, Turner M, et al. Systems analysis and improvement approach to optimize outpatient mental health treatment cascades in Mozambique (SAIA-MH): study protocol for a cluster randomized trial. Implement Sci. 2022;17(37). https://doi.org/10.1186/s13012-022-01213-8.

Swindle T, Rutledge JM, Selig JP, et al. Obesity prevention practices in early care and education settings: an adaptive implementation trial. Implement Sci. 2022;17(25). https://doi.org/10.1186/s13012-021-01185-1.

Cashin AG, McAuley JH, Lee H. Advancing the reporting of mechanisms in implementation science: a guideline for reporting mediation analyses (AGReMA). Implement Res Pract. 2022;3:26334895221105568.

Google Scholar 

Mazzucca S, Tabak RG, Pilar M, Ramsey AT, Baumann AA, Kryzer E, et al. Variation in research designs used to test the effectiveness of dissemination and implementation strategies: a review. Front Public Health. 2018;6:32. https://doi.org/10.3389/fpubh.2018.00032.

Article  PubMed  PubMed Central  Google Scholar 

Fritz MS, Mackinnon DP. Required sample size to detect the mediated effect. Psychol Sci. 2007;18:233–9. https://doi.org/10.1111/j.1467-9280.2007.01882.x.

Article  PubMed  Google Scholar 

Hayes AF, Scharkow M. The relative trustworthiness of inferential tests of the indirect effect in statistical mediation analysis: does method really matter? Psychol Sci. 2013;24:1918–27.

Article  Google Scholar 

MacKinnon DP, Lockwood CM, Hoffman JM, West SG, Sheets V. A comparison of methods to test mediation and other intervening variable effects. Psychol Methods. 2002;7:83–104. https://doi.org/10.1037/1082-989X.7.1.83.

Article  PubMed  PubMed Central  Google Scholar 

Schoemann AM, Boulton AJ, Short SD. Determining power and sample size for simple and complex mediation models. Soc Psychol Personal Sci. 2017;8:379–86. https://doi.org/10.1177/1948550617715068.

Article  Google Scholar 

Thoemmes F, Mackinnon DP, Reiser MR. Power analysis for complex mediational designs using Monte Carlo methods. Struct Equ Model. 2010;17:510–34. https://doi.org/10.1080/10705511.2010.489379.

Article  Google Scholar 

Raudenbush SW, Bryk AS. Hierarchical linear models: applications and data analysis methods. Thousand Oaks: Sage; 2002. p. 1.

Google Scholar 

Snijders TA, Bosker RJ. Multilevel analysis: an introduction to basic and advanced multilevel modeling. Thousand Oaks: Sage; 2011.

Google Scholar 

Zhang Z, Zyphur MJ, Preacher KJ. Testing multilevel mediation using hierarchical linear models: problems and solutions. Organ Res Methods. 2009;12:695–719.

Article  Google Scholar 

Krull JL, MacKinnon DP. Multilevel modeling of individual and group level mediated effects. Multivar Behav Res. 2001;36:249–77. https://doi.org/10.1207/S15327906MBR3602_06.

CAS  Article  Google Scholar 

Pituch KA, Murphy DL, Tate RL. Three-level models for indirect effects in school-and class-randomized experiments in education. J Exp Educ. 2009;78:60–95.

Article  Google Scholar 

Preacher KJ. Multilevel SEM strategies for evaluating mediation in three-level data. Psychol Methods. 2011;46:691–731. https://doi.org/10.1080/00273171.2011.589280.

Article  Google Scholar 

Preacher KJ, Zyphur MJ, Zhang Z. A general multilevel SEM framework for assessing multilevel mediation. Psychol Methods. 2010;15:209. https://doi.org/10.1037/a0020141.

Article  PubMed  Google Scholar 

Kelcey B, Spybrook J, Dong N. Sample size planning for cluster-randomized interventions probing multilevel mediation. Prev Sci. 2019;20:407–18. https://doi.org/10.1007/s11121-018-0921-6.

Article  PubMed  Google Scholar 

Kelcey B, Xie Y, Spybrook J, Dong N. Power and sample size determination for multilevel mediation in three-level cluster-randomized trials. Multivar Behav Res. 2021;56:496–513. https://doi.org/10.1080/00273171.2020.1738910.

Article  Google Scholar 

Aarons GA, Ehrhart MG, Moullin JC, et al. Testing the leadership and organizational change for implementation (LOCI) intervention in substance abuse treatment: a cluster randomized trial study protocol. Implement Sci. 2017;12(29). https://doi.org/10.1186/s13012-017-0562-3.

Wang X, Turner EL, Preisser JS, Li F. Power considerations for generalized estimating equations analyses of four-level cluster randomized trials. Biom J. 2022;64(4):663–80.

Article  Google Scholar 

Bollen KA. Structural equations with latent variables: Wiley; 1989.

Book  Google Scholar 

Gonzalez-Roma V, Hernandez A. Conducting and evaluating multilevel studies: recommendations, resources, and a checklist. Organ Res Methods. 2022. https://doi.org/10.1177/10944281211060712.

Preacher KJ, Zhang Z, Zyphur MJ. Alternative methods for assessing mediation in multilevel data: the advantages of multilevel SEM. Struct Equ Model. 2011;18:161–82. https://doi.org/10.1080/10705511.2011.557329.

Article  Google Scholar 

Lüdtke O, Marsh HW, Robitzsch A, Trautwein U, Asparouhov T, Muthén B. The multilevel latent covariate model: a new, more reliable approach to group-level effects in contextual studies. Psychol Methods. 2008;13:203–29.

Article  Google Scholar 

Muthén BO, Muthén LK, Asparouhov T. Regression and mediation analysis using Mplus. Los Angeles: Muthén & Muthén; 2017.

Google Scholar 

Muthén LK, Muthén BO. How to use a Monte Carlo study to decide on sample size and determine power. Struct Equ Model. 2002;9:599–620. https://doi.org/10.1207/S15328007SEM0904_8.

Article  Google Scholar 

Skrondal A. Design and analysis of Monte Carlo experiments: attacking the conventional wisdom. Multivar Behav Res. 2000;35:137–67. https://doi.org/10.1207/s15327906mbr3502_1.

CAS  Article  Google Scholar 

Boomsma A. Reporting Monte Carlo simulation studies in structural equation modeling. Struct Equ Model. 2013;20:518–40. https://doi.org/10.1080/10705511.2013.797839.

Article  Google Scholar 

Zhang Z. Monte Carlo based statistical power analysis for mediation models: methods and software. Behav Res Methods. 2014;46:1184–98.

Article  Google Scholar 

Cohen J. A power primer. Psychol Bull. 1992;112:155–9. https://doi.org/10.1037//0033-2909.112.1.155.

CAS  Article  PubMed  Google Scholar 

Ben Charif A, Croteau J, Adekpedjou R, Zomahoun HTV, Adisso EL, Légaré F. Implementation research on shared decision making in primary care: inventory of intracluster correlation coefficients. Med Decis Mak. 2019;39:661–72. https://doi.org/10.1177/0272989x19866296.

Article  Google Scholar 

Campbell MK, Fayers PM, Grimshaw JM. Determinants of the intracluster correlation coefficient in cluster randomized trials: the case of implementation research. Clin Trials. 2005;2:99–107. https://doi.org/10.1191/1740774505cn071oa.

Article  PubMed  Google Scholar 

Murray DM, Blitstein JL. Methods to reduce the impact of intraclass correlation in group-randomized trials. Eval Rev. 2003;27(1):79–103.

Article 

留言 (0)

沒有登入
gif