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Cited by 322Advanced Causal Inference TechniquesStatistical Methods and Bayesian InferenceReligion, Spirituality, and Psychology

The DOI matches its Crossref record; 48 of the 48 references it cites were found in a registry or an index.

Causal inference and longitudinal data: a case study of religion and mental health

VanderWeele, Tyler J., Jackson, John W., Li, Shanshan·2016·Social Psychiatry and Psychiatric Epidemiology
DOI 10.1007/s00127-016-1281-9
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Abstract

Purpose We provide an introduction to causal inference with longitudinal data and discuss the complexities of analysis and interpretation when exposures can vary over time. Methods We consider what types of causal questions can be addressed with the standard regression-based analyses and what types of covariate control and control for the prior values of outcome and exposure must be made to reason about causal effects. We also consider newer classes of causal models, including marginal structural models, that can assess questions of the joint effects of time-varying exposures and can take into account feedback between the exposure and outcome over time. Such feedback renders cross-sectional data ineffective for drawing inferences about causation. Results The challenges are illustrated by analyses concerning potential effects of religious service attendance on depression, in which there may in fact be effects in both directions with service attendance preventing the subsequent depression, but depression itself leading to lower levels of the subsequent religious service attendance. Conclusions Longitudinal designs, with careful control for prior exposures, outcomes, and confounders, and suitable methodology, will strengthen research on mental health, religion and health, and in the biomedical and social sciences generally.

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Crossref · 10.1007/s00127-016-1281-9

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  1. Rothman KJ, Greenland S, Lash TL (2008) Modern epidemiology, 3rd edn. Lippincott Williams and Wilkins, Philadelphia

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Metadata

Authors
VanderWeele, T. J., Jackson, J. W., & Li, S.
Affiliations
Harvard University (US)
Corresponding author
VanderWeele, Tyler J.
ORCID
Venue
Social Psychiatry and Psychiatric Epidemiology
Publisher
Springer Science and Business Media LLC
Published
2016-09-08
Volume
51
Issue
11
Pages
1457-1466
ISSN
  • 0933-7954 (ISSN-L)
  • 1433-9285
DOI
10.1007/s00127-016-1281-9
OpenAlex
W2510473071
Cited by
322
References
48
Citations by year
2026: 16 · 2025: 28 · 2024: 38 · 2023: 80 · 2022: 40 · 2021: 34 · 2020: 37 · 2019: 18 · 2018: 18 · 2017: 10 · 2016: 3
FWCI
2.31
Type
journal article
Language
en
Open access
closed
Licence
Locations
  • Social Psychiatry and Psychiatric Epidemiology (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • John Templeton Foundation (52125)
  • National Institute of Environmental Health Sciences (ES017876)
Topics
  • Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
  • Social Sciences › Health › Religion, Spirituality, and Psychology
Keywords
causal inference, longitudinal data, time-varying exposure, marginal structural models, religious service attendance, depression, religion and mental health, confounding adjustment, causal effects
MeSH terms
Cross-Sectional Studies, Depressive Disorder, Humans, Mental Health, Religion, Research Design

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