Evaluating a Method to Estimate Mediation Effects With Discrete-Time Survival Outcomes
The utility of evaluating mediation effects spans across research domains. The model facilitates investigation of underlying mechanisms of event timing and, as such, has the potential to help strengthen etiological research and inform intervention work that incorporates the evaluation of mediating v...
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doaj-f983e6c667b84f59a9a41a3e1a0bd9192020-11-25T00:12:53ZengFrontiers Media S.A.Frontiers in Psychology1664-10782019-04-011010.3389/fpsyg.2019.00740436199Evaluating a Method to Estimate Mediation Effects With Discrete-Time Survival OutcomesAmanda Jane Fairchild0Chao Cai1Heather McDaniel2Dexin Shi3Amanda Gottschall4Katherine E. Masyn5Department of Psychology, University of South Carolina, Columbia, SC, United StatesDepartment of Psychology, University of South Carolina, Columbia, SC, United StatesCurry School of Education, University of Virginia, Charlottesville, VA, United StatesDepartment of Psychology, University of South Carolina, Columbia, SC, United StatesDepartment of Psychology, University of South Carolina, Columbia, SC, United StatesDepartment of Population Health Sciences, Georgia State University, Atlanta, GA, United StatesThe utility of evaluating mediation effects spans across research domains. The model facilitates investigation of underlying mechanisms of event timing and, as such, has the potential to help strengthen etiological research and inform intervention work that incorporates the evaluation of mediating variables. In order for the analyses to be maximally useful however, it is critical to employ methodology appropriate for the data under investigation. The purpose of this paper is to evaluate a regression-based approach to estimating mediation effects with discrete-time survival outcomes. We empirically evaluate the performance of the discrete-time survival mediation model in a statistical simulation study, and demonstrate that results are functionally equivalent to estimates garnered from a potential-outcomes framework. Simulation results indicate that parameter estimates of mediation in the model were statistically accurate and precise across the range of examined conditions. Type 1 error rates were also tolerable in the conditions studied. Adequate power to detect effects in the model, with binary X and continuous M variables, required effect sizes of the mediation paths to be medium or large. Possible extensions of the model are also considered.https://www.frontiersin.org/article/10.3389/fpsyg.2019.00740/fullevent historydiscrete-timesurvival analysismediationonset |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Amanda Jane Fairchild Chao Cai Heather McDaniel Dexin Shi Amanda Gottschall Katherine E. Masyn |
spellingShingle |
Amanda Jane Fairchild Chao Cai Heather McDaniel Dexin Shi Amanda Gottschall Katherine E. Masyn Evaluating a Method to Estimate Mediation Effects With Discrete-Time Survival Outcomes Frontiers in Psychology event history discrete-time survival analysis mediation onset |
author_facet |
Amanda Jane Fairchild Chao Cai Heather McDaniel Dexin Shi Amanda Gottschall Katherine E. Masyn |
author_sort |
Amanda Jane Fairchild |
title |
Evaluating a Method to Estimate Mediation Effects With Discrete-Time Survival Outcomes |
title_short |
Evaluating a Method to Estimate Mediation Effects With Discrete-Time Survival Outcomes |
title_full |
Evaluating a Method to Estimate Mediation Effects With Discrete-Time Survival Outcomes |
title_fullStr |
Evaluating a Method to Estimate Mediation Effects With Discrete-Time Survival Outcomes |
title_full_unstemmed |
Evaluating a Method to Estimate Mediation Effects With Discrete-Time Survival Outcomes |
title_sort |
evaluating a method to estimate mediation effects with discrete-time survival outcomes |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Psychology |
issn |
1664-1078 |
publishDate |
2019-04-01 |
description |
The utility of evaluating mediation effects spans across research domains. The model facilitates investigation of underlying mechanisms of event timing and, as such, has the potential to help strengthen etiological research and inform intervention work that incorporates the evaluation of mediating variables. In order for the analyses to be maximally useful however, it is critical to employ methodology appropriate for the data under investigation. The purpose of this paper is to evaluate a regression-based approach to estimating mediation effects with discrete-time survival outcomes. We empirically evaluate the performance of the discrete-time survival mediation model in a statistical simulation study, and demonstrate that results are functionally equivalent to estimates garnered from a potential-outcomes framework. Simulation results indicate that parameter estimates of mediation in the model were statistically accurate and precise across the range of examined conditions. Type 1 error rates were also tolerable in the conditions studied. Adequate power to detect effects in the model, with binary X and continuous M variables, required effect sizes of the mediation paths to be medium or large. Possible extensions of the model are also considered. |
topic |
event history discrete-time survival analysis mediation onset |
url |
https://www.frontiersin.org/article/10.3389/fpsyg.2019.00740/full |
work_keys_str_mv |
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