caa a22 4500 606153349 CHVBK 20210128100553.0 cr unu---uuuuu 210128e20151001xx s 000 0 eng 10.1007/s11121-014-0489-8 doi (NATIONALLICENCE)springer-10.1007/s11121-014-0489-8 Sample Size Considerations in Prevention Research Applications of Multilevel Modeling and Structural Equation Modeling [Elektronische Daten] [Rick Hoyle, Nisha Gottfredson] When the goal of prevention research is to capture in statistical models some measure of the dynamic complexity in structures and processes implicated in problem behavior and its prevention, approaches such as multilevel modeling (MLM) and structural equation modeling (SEM) are indicated. Yet the assumptions that must be satisfied if these approaches are to be used responsibly raise concerns regarding their use in prevention research involving smaller samples. In this article, we discuss in nontechnical terms the role of sample size in MLM and SEM and present findings from the latest simulation work on the performance of each approach at sample sizes typical of prevention research. For each statistical approach, we draw from extant simulation studies to establish lower bounds for sample size (e.g., MLM can be applied with as few as ten groups comprising ten members with normally distributed data, restricted maximum likelihood estimation, and a focus on fixed effects; sample sizes as small as N = 50 can produce reliable SEM results with normally distributed data and at least three reliable indicators per factor) and suggest strategies for making the best use of the modeling approach when N is near the lower bound. Society for Prevention Research, 2014 Sample size nationallicence Multilevel modeling nationallicence Structural equation modeling nationallicence Hoyle Rick Department of Psychology and Neuroscience, Duke University, 27708, Durham, NC, USA aut Gottfredson Nisha Center for Developmental Science, University of North Carolina at Chapel Hill, 27599, Chapel Hill, NC, USA aut Prevention Science Springer US; http://www.springer-ny.com 16/7(2015-10-01), 987-996 1389-4986 16:7<987 2015 16 11121 https://doi.org/10.1007/s11121-014-0489-8 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s11121-014-0489-8 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Hoyle Rick Department of Psychology and Neuroscience, Duke University, 27708, Durham, NC, USA aut NATIONALLICENCE 700 1- Gottfredson Nisha Center for Developmental Science, University of North Carolina at Chapel Hill, 27599, Chapel Hill, NC, USA aut NATIONALLICENCE 773 0- Prevention Science Springer US; http://www.springer-ny.com 16/7(2015-10-01), 987-996 1389-4986 16:7<987 2015 16 11121