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A Class of Distribution-Free Models for Longitudinal Mediation Analysis

Published online by Cambridge University Press:  01 January 2025

D. Gunzler ,
W. Tang ,
N. Lu ,
P. Wu  and
X. M. Tu
D. Gunzler*
Affiliation:
Case Western Reserve University at MetroHealth Medical Center
W. Tang
Affiliation:
University of Rochester
N. Lu
Affiliation:
University of Rochester and Canandaigua VA Medical Center
P. Wu
Affiliation:
Christiana Care Health System
X. M. Tu
Affiliation:
University of Rochester and Canandaigua VA Medical Center
*
Requests for reprints should be sent to D. Gunzler, Center for Health Care Research & Policy, Case Western Reserve University at MetroHealth Medical Center, 2500 MetroHealth Drive, Cleveland, OH 44109-1998, USA. E-mail: dgunzler@metrohealth.org
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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.

Keywords

mediation analysisfunctional response modelsstructural equation modelweighted generalized estimating equations IImissing datageneralized least squares
Type
Original Paper
Information
Psychometrika , Volume 79 , Issue 4 , October 2014 , pp. 543 - 568
Copyright
Copyright © 2013 The Psychometric Society

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