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. Speyer, L.G., Zhu, X., Yang, Y., Ribeaud, D. & Eisner, M. (2024).

This website is a supplement to “Three Extensions of the Random Intercept Cross-Lagged Panel Model” by Mulder and Hamaker (2021). It contains Mplus syntax and lavaan (R-package) code for specifying the basic RI-CLPM and the following three extensions: using multiple indictors for …

The random intercept cross-lagged panel model (RI-CLPM) proposed by Hamaker et al. (2015) is an extension of the traditional cross-lagged panel model (CLPM). It was introduced to account for stable, trait-like differences between units (e.g., individuals, dyads, families, etc.), such that the lagged relations pertain exclusively to within-unit ...

2020年8月11日 · This paper discusses three extensions of the RI-CLPM that researchers may be interested in, but are unsure of how to accomplish: (a) including stable, person-level characteristics as predictors and/or outcomes; (b) specifying a multiple-group version; and (c) including multiple indicators.

In Part 2, we introduced the RI-CLPM model, which is suited for estimation of these effects due to its flexibility in accounting for both autoregression, bidirectionality and between-person differences at the same time.

With Mplus version 8.7 and later, it is possible to estimate the RI-CLPM for binary and ordinal variables as well (Asparouhov and Muthén 2021). Compared to the RI-CLPM for continuous variables, there are two important differences: A Bayesian estimator or WLSMV estimator (with theta parametrization) is needed.

The RI-CLPM. To specify the RI-CLPM we need four parts. A between part, consisting of the random intercepts. It is specified using the =~ command, RIx =~ 1*x1 + 1*x2 ..., where 1* fixes the factor loading to one. A within part, consisting of within-unit fluctuations. It is also specified using the =~ command, wx1 =~ 1*x1; wx2 =~ 1*x2; ....

The development of the random intercept cross-lagged panel model (RI-CLPM) is an extension of the traditional cross-lagged panel model (CLPM), which aims to study between and within person variances in longitudinal data.

How to run the RI‐CLPM with Mplus By Ellen Hamaker March 21, 2018 The random intercept cross‐lagged panel model (RI‐CLPM) as proposed by Hamaker, Kuiper and Grasman (2015, Psychological Methods) is a model that decomposes each observed score into a between‐person part and a within‐person part.

The random intercept cross-lagged panel model (RI-CLPM) is rapidly gaining popularity in psychology and related fields as a structural equation modeling (SEM) approach to longitudinal data. It decomposes observed scores into within-unit …