Cross-Sectional Analysis of Longitudinal Mediation Processes
2018/04/06 by Kristine D. O'Laughlin, Kristine D. O’Laughlin, Monica J. Martin +1 · 439 citations
Mathematics · Psychology · Social Sciences · #Computer science #Cultural Differences and Values #Data mining #Econometrics #Longitudinal data #Longitudinal study #Mathematics #Mediation #Mental Health Research Topics #Psychology #Social and Intergroup Psychology #Social science #Sociology #Statistics #Structural equation modeling
paper · doi:10.1080/00273171.2018.1454822
published in Multivariate Behavioral Research 53(3), 375-402 (Taylor & Francis)
openalex publication_date 2018/04/06 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01
Abstract
Statistical mediation analysis can help to identify and explain the mechanisms behind psychological processes. Examining a set of variables for mediation effects is a ubiquitous process in the social sciences literature; however, despite evidence suggesting that cross-sectional data can misrepresent the mediation of longitudinal processes, cross-sectional analyses continue to be used in this manner. Alternative longitudinal mediation models, including those rooted in a structural equation modeling framework (cross-lagged panel, latent growth curve, and latent difference score models) are currently available and may provide a better representation of mediation processes for longitudinal data. The purpose of this paper is twofold: first, we provide a comparison of cross-sectional and longitudinal mediation models; second, we advocate using models to evaluate mediation effects that capture the temporal sequence of the process under study. Two separate empirical examples are presented to illustrate differences in the conclusions drawn from cross-sectional and longitudinal mediation analyses. Findings from these examples yielded substantial differences in interpretations between the cross-sectional and longitudinal mediation models considered here. Based on these observations, researchers should use caution when attempting to use cross-sectional data in place of longitudinal data for mediation analyses.
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