James Peugh, PhD, is Director of Quantitative Services in the Division of Behavioral Medicine and Clinical Psychology, Cincinnati Childrens Hospital Medical Center, and Research Professor in the Department of Pediatrics at the University of Cincinnati Medical School. His methodological interests focus on the use of Monte Carlo simulation techniques to test advanced statistical analyses. Dr. Peugh has also published pedagogical "how-to" papers demonstrating the application of statistical techniques. He has publications in a variety of quantitative, educational, and psychological journals.
Kaylee Litson, PhD, is Assistant Professor in the Department of Psychology at the University of Houston. As an interdisciplinary quantitative psychologist, they have a particular interest in the link between statistical model estimation and theory-driven interpretation, especially in the context of complex, multimethod, and longitudinal research design. Dr. Litsons work highlights the translation of quantitative psychology methods to applied research in fields such as cognition and educational psychology. Their publications have appeared in applied and quantitative journals.
Description
Planning effective research investigations requires sophisticated power analysis techniques. This book provides readers with clearly explained tools for using Monte Carlo simulations to estimate the needed sample sizes for adequate statistical power for a variety of modern research designs. Featuring step-by-step instructions, chapters move from simpler cross-sectional designs and path tracing rules to advanced longitudinal designs, while incorporating mediation, moderation, and missing data considerations. Worked-through applied examples with annotated Mplus and R syntax scripts, sample power analysis write-ups, and end-of-chapter suggested readings are also included. The companion website offers Mplus and R code for four additional power analysis models--latent variable moderation, discrete- and continuous-time survival analyses, cross-sectional and longitudinal two-level models, and moderated mediation--as well as supplemental computational materials.