Cross-Lagged Panel Analysis Using Structural Equation Modeling: Trends and Suggestions Based on a Literature Review of 111 Studies

Cross-lagged panel analysis based on structural equation modeling (SEM) has been widely used in the behavioral sciences. The present study provides a literature review based on 111 studies published in major psychology journals that conducted cross-lagged panel analysis. Through this review, we offer an overview of current trends in study design, analytical methods (e.g., estimation method, missing data handling), and model selection, and discuss practical challenges and implications for future applications. A major finding is that the use of the RI-CLPM has increased substantially (41% of the studies) over the past few years. At the same time, most studies rely on longitudinal data with a small number of measurement occasions (e.g., T=3,4). Studies employing the RI-CLPM tend to conduct only limited comparisons with potential alternative models. Among the studies that used summed scores based on psychological scales, many did not report or examine whether longitudinal measurement invariance was supported.