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Objective
Background
Understanding interdependencies among people and constructs is a central interest in relationship science. Addressing such research questions requires complex designs ideally using data collected at multiple measurement occasions of multiple constructs from at least two persons (e.g., both partners of a couple). The Cross-Lagged Panel Model (CLPM) has been widely used to analyze such data, however, particularly during the last decade, it has been pointed out that the CLPM confounds between- and within-person variation. As a consequence, alternative models such as the Random-Intercept Cross-Lagged Panel Model (RI-CLPM) and the Latent Curve Model with Structured Residuals (LCM-SR) were proposed that aim to disentangle between- and within-person variation and, hence, allow conclusions regarding within-person dynamics.
Method
As an illustrative example, we apply dyadic extensions of the CLPM, RI-CLPM, and LCM-SR to investigate the dynamic interplay between depression and relationship satisfaction in a sample of 1699 mixed-gender couples surveyed in the German Family Panel.
Results
While the CLPM indicated a reciprocal relationship between depression and satisfaction, the RI-CLPM and LCM-SR indicated a unidirectional association flowing from depression to satisfaction.
Conclusion
We discuss how findings like this can foster theory-building and, ultimately, strengthen relationship science.
