Statistical Models for the Inference of Within-person Relations: A Random Intercept Cross-Lagged Panel Model and Its Interpretation

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  • 個人内関係の推測と統計モデル：ランダム切片交差遅延パネルモデルを巡って

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<p>Since Hamaker, Kuiper, and Grasman's (2015) critique, the random intercept cross-lagged panel model (RI-CLPM), which includes stable trait factors as unobserved heterogeneity to reveal within-person processes, has been widely applied in psychology. However, although various longitudinal models that examine reciprocal relations exist in different contexts and disciplines, their conceptual and mathematical relations have not been well recognized, and scholars continue to discuss the issues of model comparison and model choice. This study provides an overview of the RI-CLPM and then introduces other longitudinal models to explain their relations as well as potential difficulties to infer within-person processes. It describes that stable trait factors with time-invariant impacts on observations are modeled separately from regression models, making this factor conceptually and mathematically different from common factors in many other models. We also highlight that the presumed uncorrelatedness between stable trait factors and within-person processes is the key to understanding the RI-CLPM and how it is mathematically related to dynamic panel models, which could be a useful candidate.</p>

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Details 詳細情報について

  • CRID
    1390015191534520064
  • DOI
    10.11201/jjdp.33.267
  • ISSN
    21879346
    09159029
  • Text Lang
    ja
  • Data Source
    • JaLC
  • Abstract License Flag
    Disallowed

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