Cross-Sectional Analysis of Longitudinal Mediation Processes
| Autor: | Monica J. Martin, Emilio Ferrer, Kristine D. O’Laughlin |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Statistics and Probability
Male Mediation (statistics) Adolescent Longitudinal data Cross-sectional study Process (engineering) Psychology Adolescent Mothers Experimental and Cognitive Psychology Models Psychological Difference score Structural equation modeling 03 medical and health sciences Young Adult 0302 clinical medicine 0504 sociology Arts and Humanities (miscellaneous) Hostility Use caution Humans Longitudinal Studies Set (psychology) Maternal Behavior Motivation Models Statistical 05 social sciences 050401 social sciences methods General Medicine Self Concept Affect Cross-Sectional Studies Data Interpretation Statistical Female Psychology 030217 neurology & neurosurgery Cognitive psychology |
| Zdroj: | Multivariate behavioral research. 53(3) |
| ISSN: | 1532-7906 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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