Optimizing Detection of True Within-Person Effects for Intensive Measurement Designs: A Comparison of Multilevel SEM and
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Optimizing Detection of True Within-Person Effects for Intensive Measurement Designs: A Comparison of Multilevel SEM and Unit-Weighted Scale Scores Jonathan Rush 1
&
Philippe Rast 2 & Scott M. Hofer 1
# The Psychonomic Society, Inc. 2020
Abstract Intensive repeated measurement designs are frequently used to investigate within-person variation over relatively brief intervals of time. The majority of research utilizing these designs relies on unit-weighted scale scores, which assume that the constructs are measured without error. An alternative approach makes use of multilevel structural equation models (MSEM), which permit the specification of latent variables at both within-person and between-person levels. These models disaggregate measurement error from systematic variance, which should result in less biased within-person estimates and larger effect sizes. Differences in power, precision, and bias between multilevel unit-weighted models and MSEMs were compared through a series of Monte Carlo simulations. Results based on simulated data revealed that precision was consistently poorer in the MSEMs than the unitweighted models, particularly when reliability was low. However, the degree of bias was considerably greater in the unitweighted model than the latent variable model. Although the unit-weighted model consistently underestimated the effect of a covariate, it generally had similar power relative to the MSEM model due to the greater precision. Considerations for scale development and the impact of within-person reliability are highlighted. Keywords Multilevel modeling . within-person effects . power . multilevel structural equation modeling . composite scores
Intensive repeated measurement designs (e.g., daily diary, ecological momentary assessment) are frequently used in psychological research to investigate within-person variation over relatively brief intervals of time (e.g., hours, days, or weeks). These designs allow variance to be partitioned into withinperson and between-person sources of variability, enabling differential effects to be estimated at the within-person and between-person level of analysis (e.g., Curran & Bauer, 2011; Hoffman & Stawski, 2009; Sliwinski, 2008). Much research has examined within-person covariation of timeResearch reported in this manuscript was supported by the National Institute on Aging of the National Institutes of Health, Grant R01AG050720 and P01AG043362. Jonathan Rush was supported by a Joseph Armand Bombardier Doctoral Scholarship from the Social Sciences and Humanities Research Council of Canada. * Jonathan Rush [email protected] 1
Department of Psychology, University of Victoria, P.O. Box 1700, STN CSC, Victoria, BC V8W 2Y2, Canada
2
Department of Psychology, University of California, Davis, Davis, CA, USA
varying constructs to identify how variables travel dynamically together across time. These covariations have been examined in a variety of domains to identify reliable short-term within-person associations. For example, Hoppman and Klumb (2006) examined daily
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