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A Class of Distribution-Free Models for Longitudinal Mediation Analysis

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  • D. Gunzler
  • W. Tang
  • N. Lu
  • P. Wu
  • X. Tu

Abstract

Mediation analysis constitutes an important part of treatment study to identify the mechanisms by which an intervention achieves its effect. Structural equation model (SEM) is a popular framework for modeling such causal relationship. However, current methods impose various restrictions on the study designs and data distributions, limiting the utility of the information they provide in real study applications. In particular, in longitudinal studies missing data is commonly addressed under the assumption of missing at random (MAR), where current methods are unable to handle such missing data if parametric assumptions are violated. In this paper, we propose a new, robust approach to address the limitations of current SEM within the context of longitudinal mediation analysis by utilizing a class of functional response models (FRM). Being distribution-free, the FRM-based approach does not impose any parametric assumption on data distributions. In addition, by extending the inverse probability weighted (IPW) estimates to the current context, the FRM-based SEM provides valid inference for longitudinal mediation analysis under the two most popular missing data mechanisms; missing completely at random (MCAR) and missing at random (MAR). We illustrate the approach with both real and simulated data. Copyright The Psychometric Society 2014

Suggested Citation

  • D. Gunzler & W. Tang & N. Lu & P. Wu & X. Tu, 2014. "A Class of Distribution-Free Models for Longitudinal Mediation Analysis," Psychometrika, Springer;The Psychometric Society, vol. 79(4), pages 543-568, October.
    • Handle: RePEc:spr:psycho:v:79:y:2014:i:4:p:543-568
    DOI: 10.1007/s11336-013-9355-z
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    References listed on IDEAS

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    3. Junichi Hirose & Koji Kotani & Shunsuke Managi, 2023. "How do autonomy and inquisitiveness play roles in sustainable development? Implications from matrilineal Island Palau," Working Papers SDES-2023-1, Kochi University of Technology, School of Economics and Management, revised Feb 2023.
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    5. Junichi Hirose & Koji Kotani, 2021. "How does inquisitiveness matter for generativity and happiness?," Working Papers SDES-2021-3, Kochi University of Technology, School of Economics and Management, revised May 2021.

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