Data from: A Causal Mediation Model for Studying Longitudinal Animal Behavior and Survival Outcomes

Li, Fan; Zeng, Shuxi; Alberts, Susan C; Archie, Elizabeth A; Lange, Elizabeth C; Campos, Fernando A

Data from: A Causal Mediation Model for Studying Longitudinal Animal Behavior and Survival Outcomes

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Causal mediation analysis studies how the treatment effect of an exposure on outcomes is mediated through intermediate variables. Although many applications involve longitudinal data, the existing methods are not directly applicable to settings where the mediators are measured on irregular time grids. In this paper, we propose a causal mediation method that accommodates longitudinal mediators on arbitrary time grids and survival outcomes simultaneously. We take a functional data analysis perspective and view longitudinal mediators as realizations of underlying smooth stochastic processes. We define causal estimands of direct and indirect effects accordingly and provide corresponding identification assumptions. We employ a functional principal component analysis approach to estimate the mediator process, and propose a Cox hazard model for the survival outcome that flexibly adjusts the mediator process. We then derive a g-computation formula to express the causal estimands using the model coefficients. The proposed method is applied to a longitudinal data set from the Amboseli Baboon Research Project to investigate the causal relationships between early adversity, adult physiological stress responses, and survival among wild female baboons. We find that adversity experienced in early life has a significant direct effect on females' life expectancy and survival probability, but find little evidence that these effects were mediated by markers of the stress response in adulthood. We further developed a sensitivity analysis method to assess the impact of potential violation to the key assumption of sequential ignorability. ... [Read More]

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Zeng, S., Lange, E., Archie, E., Campos, F., Alberts, S., & Li, F. (2021). Data from: A causal mediation model for studying longitudinal animal behavior and survival outcomes. Duke Research Data Repository. https://doi.org/10.7924/r4td9ws23

Creator: Li, Fan
Zeng, Shuxi
Alberts, Susan C
Archie, Elizabeth A
Lange, Elizabeth C
Campos, Fernando A
DOI: 10.7924/r4td9ws23
Subject: Functional principal component analysis
Causal inference
Mediation
Functional data
Publication Date: September 27, 2021
ARK: ark:/87924/r4td9ws23
Contributor: Mututua, R. S.
Siodi, L.I.
Warutere, J.K.
Sayialel, S.N.
Affiliation: Evolutionary Anthropology
Department of Antropology, University of Texas at San Antonio
Statistical Science
Department of Biological Sciences, University of Notre Dame
Biology
Publisher: Duke Research Data Repository
Collection Dates: 2001-2018
Type: Dataset
Format: CSV
Related Materials: Zeng, S., Lange, E.C., Archie, E.A. et al. (2022). A Causal Mediation Model for Longitudinal Mediators and Survival Outcomes with an Application to Animal Behavior. JABES. https://doi.org/10.1007/s13253-022-00490-6
Funding Agency: National Institute on Aging
Grant Number: R01AG053308
Contact: Susan Alberts, 0000-0002-1313-488X, alberts@duke.edu
Elizabeth Lange, 0000-0001-6834-9207, ecl32@duke.edu
License: Creative Commons CC0 1.0 Universal
Title: Data from: A Causal Mediation Model for Studying Longitudinal Animal Behavior and Survival Outcomes
License: http://creativecommons.org/publicdomain/zero/1.0/
Repository: Duke Research Data Repository

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	GC_survival_data.csv	2021-09-27	Public	Download
	GC_Survival_Readme.txt	2021-09-27	Public	Download

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