Random Intercept Cross-Lagged Panel Models (RI-CLPM)

Mplus Web Talks

• Web Talk 4.1: Using Mplus To Do Cross-Lagged Modeling of Panel Data, Part 1: Continuous Variables., November 2021.
  
  
• Web Talk 4.2: Using Mplus To Do Cross-Lagged Modeling of Panel Data, Part 2: Categorical Variables., April 2022.
  
  
• Web Talk 5: Can Cross-Lagged Panel Modeling Be Relied On to Establish Cross-Lagged Effects?, November 2022.
  
  

  RI-CLPM Theory

• Muthén, B. & Asparouhov, T. (2024). Can cross-lagged panel modeling be relied on to establish cross-lagged effects? The case of contemporaneous and reciprocal effects. Psychological Methods. DOI: 10.1037/met0000661 (Supplementary Materials).
  
  
• Tseng, M. (2024). Latent interaction effect in the CLPM model: A two-step multiple imputation analysis. Structural Equation Modeling: A Multidisciplinary Journal, 1–10. DOI: 10.1080/10705511.2024.2374349
  
  
• Muthén, B., Asparouhov, T. & Witkiewitz, K. (2024). Cross-lagged panel modeling with binary and ordinal outcomes. Advance online publication. DOI: 10.1037/met0000701 (Supplementary Materials).
  
  
• Mulder, J.D. & Hamaker, E.L. (2020). Three extensions of the Random Intercept Cross-Lagged Panel Model. Structural Equation Modeling: A Multidisciplinary Journal, DOI: 10.1080/10705511.2020.1784738
  
  
• Hamaker, E. L., Kuiper, R. M., & Grasman, R. P. P. P. (2015). A critique of the cross-lagged panel model. Psychological Methods, 20(1), 102-116. DOI: 10.1037/a0038889
  
  

  Mplus Scripts

• Mplus scripts for the RI-CLPM and three extensions: time-invariant variables in RI-CLPM, multiple group RI-CLPM, and multiple indicator or latent RI-CLPM.
  
  

  Related Papers

• Speyer, L.G., Zhu, X., Yang, Y., Ribeaud, D. & Eisner, M. (2024). On the Importance of Considering Concurrent Effects in Random-Intercept Cross-Lagged Panel Modelling: Example Analysis of Bullying and Internalising Problems. Multivariate Behavioral Research. DOI: 10.1080/00273171.2024.2428222
  
  
• Marsh, H.W., Guo, J., Pekrun, R., Lüdtke, O. & Núñez-Regueiro, F. (2024). Cracking Chicken-Egg Conundrums: Juxtaposing Contemporaneous and Lagged Reciprocal Effects Models of Academic Self Concept and Achievement’s Directional Ordering. Educational Psychological Review. DOI: 10.1007/s10648-024-09887-w
  
  
• Tseng, M. (2024). Fitting Cross-Lagged Panel Models with the Residual Structural Equations Approach. Structural Equation Modeling: A Multidisciplinary Journal, DOI: 10.1080/10705511.2023.2296862
  
  
• Muthén, B., Asparouhov, T. & Witkiewitz, K. (2023). Cross-lagged panel modeling with categorical outcomes. Version 3. Submitted for publication. (Supplementary Materials).
  
  
• Speyer, L.G., Ushakova, A., Blakemore, S-J., Murrah, A.L. and Kievit, R. (2023). Testing for Within X Within and Between X Within moderation using random intercept cross-lagged panel models. Structural Equation Modeling: A Multidisciplinary Journal. 30(2), 315-327. DOI: 10.1080/10705511.2022.2096613
  
  
• Mulder, J. D. (2022). Power Analysis for the Random Intercept Cross-Lagged Panel Model Using the powRICLPM R-Package. Structural Equation Modeling: A Multidisciplinary Journal. DOI: 10.1080/10705511.2022.2122467
  
  
• Braun, L., Göllner, R., Rieger, S., Trautwein, U. and Spengler, M. (2021). How state and trait versions of self-esteem and depressive symptoms affect their interplay: A longitudinal experimental investigation Journal of Personality and Social Psychology: Personality Process and Individual Differences, 120(1), 206-255, DOI: 10.1037/pspp0000295
  
  
• Shamsollahi, A., Zyphur, M.J., & Ozkok, O. (2021). Long-Run Effects in Dynamic Systems: New Tools for Cross-Lagged Panel Models. Organizational Research Methods. DOI: 10.1177/1094428121993228
  
  
• Ozkok, O., Vaulont, M.J., Zyphur, M.J., Zhang, Z., Preacher, K.J., Koval, P., & Zheng, Y. (2021). Interaction Effects in Cross-Lagged Panel Models: SEM with Latent Interactions Applied to Work-Family Conflict, Job Satisfaction, and Gender. Organizational Research Methods. DOI: 10.1177/10944281211043733
  
  
• Zyphur, M.J., Allison, P.D., Tay, L. Voelkle, M.C., Preacher, K.J., Zhang, Z., Hamaker, E.L., Shamsollahi, A., Pierides, D.C., Koval, P. & Diener, E. (2020). From data to causes I: Building a general cross-lagged panel model (GCLM). Organizational Research Methods, 23(4), 651-687.
  
  
• Zyphur, M.J., Allison, P.D., Tay, L. Voelkle, M.C., Preacher, K.J., Zhang, Z., Hamaker, E.L., Shamsollahi, A., Pierides, D.C., Koval, P. & Diener, E. (2020). From data to causes II: Comparing approaches to panel data analysis. Organizational Research Methods, 23(4), 688-716.
  
  
• Usami, S. (2020). On the differences between General Cross-Lagged Panel Model and Random-Intercept Cross-Lagged Panel Model: Interpretation of Cross-Lagged parameters and model choice. Structural Equation Modeling: A Multidisciplinary Journal. DOI:10.1080/10705511.2020.1821690
  
  
• Usami, S., Murayama, K., & Hamaker, E.L. (2019). A unified framework of longitudinal models to examine reciprocal relations. Psychological Methods, 24(4), 637-657. DOI: 10.1037/met0000210
  
  
• Keijsers, L. (2015). Parental monitoring and adolescent problem behaviors: How much do we really know? International Journal of Behavioral Development, 40(3). DOI: 10.1177/0165025415592515