对应CLPM的Mplus语句为: TITLE: Cross-Lagged Panel Model, 2 variables, 2 waves; DATA: FILE IS 123.dat; ! 数据来源 VARIABLE: NAME ARE x1 x2 y1 y2; ! 变量名称 MISSING=ALL(99); ! 定义缺失值 USEVARIABLE ARE x1 x2 y1 y2; ! 使用变量 ANALYSIS: ESTIMATOR=MLR; ! 估计方法,可以自己数据...
在探索时间序列变量间的复杂交互关系时，交叉滞后面板模型（Cross-Lagged Panel Model, CLPM）显得尤为重要。它不仅关注同步相关、自回归效应，还深入分析了跨时间点的交叉滞后效应。CLPM的核心在于揭示预测性动态，但潜在的挑战在于区分个体间和个体内效应，可能导致混淆。为克服这一局限，Hamaker等人提出的随...
Mplus—随机截距交叉滞后模型www.zhihu.com/column/c_1598628283851153408 简介 关于多指标随机截距交叉滞后模型(Multiple Indicator Random Intercept Cross-Lagged Panel Model, MI RI-CLPM),在下面这篇文章的“Extension 3: The multiple indicator RI-CLPM”部分有相应介绍,感兴趣的可以仔细阅读一下。 Mulder, J...
Random Intercept Cross-Lagged Panel Models (RI-CLPM) Mplus Web Talks Web Talk 5:Can Cross-Lagged Panel Modeling Be Relied On to Establish Cross-Lagged Effects?, November 2022. RI-CLPM Theory
Am I running the correct syntax to examine 2 variables at 3 time points in a cross-lagged panel analysis? Syntax is below: VARIABLE: NAMES are PCL2 PCL3 PCL4 AC2 AC3 AC4; MISSING is PCL2(999) PCL3 (999) PCL4 (999) AC2 (999) AC3 (999) AC4 (999); ANALYSIS: type=general...
Cross-lagged panel models (CLPMs) are widely used to test mediation with longitudinal panel data. One major limitation of the CLPMs is that the model effects are assumed to be fixed across individuals. This assumption is likely to be violated (i.e., the model effects are random across indi...
One of the most popular models for investigating longitudinal associations between multiple repeatedly measured variables is the Cross-Lagged Panel Model (CLPM) and its extension, the Random-Interc...
Random intercept cross-lagged panel modelLatent curve modelReciprocal relationsStructured residualsSmushed effectsLongitudinal structural equation modelingLongitudinal data can provide inferences at both the between-person and within-person levels of analysis, but only to the extent that the statistical models ...
The question is what estimator should I use when I use cross-lagged panel to analysis my data? ML? MLM? ps. I had used the ML to conduct cross-lagged but the model fit are really poor. Then, I changed the estimator to MLM, the model fit are much better. Linda K. Muthen posted...
I am building autoregressive cross-lagged model in mplus to identify the relations between 3 sets of (dummy) variables across 3 waves. The data in question is calendar data (control group included).Is autoregressive cross-lagged model appropriate for this data (N=300)? Tihomir Asparouhov post...