An Exponential Decay Model for Mediation

Mediation analysis is often used to investigate mechanisms of change in prevention research. Results finding mediation are strengthened when longitudinal data are used because of the need for temporal precedence. Current longitudinal mediation models have focused mainly on linear change, but many va...

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Bibliographic Details
Published in:Prevention science 2014-10, Vol.15 (5), p.611-622
Main Author: Fritz, Matthew S.
Format: Article
Language:English
Subjects:
Adolescent
Adolescent Behavior
Biological and medical sciences
Child and School Psychology
Female
General aspects
Growth models
Health Psychology
Humans
Interventionism
Longitudinal studies
Male
Mediation
Medical sciences
Medicine
Medicine & Public Health
Negotiating
Non-linear models
Nonlinear Dynamics
Planification. Prevention (methods). Intervention. Evaluation
Polynomials
Prevention
Public Health
Public health. Hygiene
Public health. Hygiene-occupational medicine
Steroids - administration & dosage
Variables
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Summary:Mediation analysis is often used to investigate mechanisms of change in prevention research. Results finding mediation are strengthened when longitudinal data are used because of the need for temporal precedence. Current longitudinal mediation models have focused mainly on linear change, but many variables in prevention change nonlinearly across time. The most common solution to nonlinearity is to add a quadratic term to the linear model, but this can lead to the use of the quadratic function to explain all nonlinearity, regardless of theory and the characteristics of the variables in the model. The current study describes the problems that arise when quadratic functions are used to describe all nonlinearity and how the use of nonlinear functions, such as exponential decay, address many of these problems. In addition, nonlinear models provide several advantages over polynomial models including usefulness of parameters, parsimony, and generalizability. The effects of using nonlinear functions for mediation analysis are then discussed and a nonlinear growth curve model for mediation is presented. An empirical example using data from a randomized intervention study is then provided to illustrate the estimation and interpretation of the model. Implications, limitations, and future directions are also discussed.
ISSN:1389-4986
1573-6695
DOI:10.1007/s11121-013-0390-x