Darssan, D, Mishra, GD, Greenwood, DC orcid.org/0000-0001-7035-3096 et al. (10 more authors) (2021) Meta-analysis for individual participant data with a continuous exposure: a case study. Journal of Clinical Epidemiology, 140. pp. 79-92. ISSN 0895-4356
Abstract
Objective
Methods for meta-analysis of studies with individual participant data and continuous exposure variables are well described in the statistical literature but are not widely used in clinical and epidemiological research. The purpose of this case study is to make the methods more accessible.
Study Design and Setting
A two-stage process is demonstrated. Response curves are estimated separately for each study using fractional polynomials. The study-specific curves are then averaged pointwise over all studies at each value of the exposure. The averaging can be implemented using fixed effects or random effects methods.
Results
The methodology is illustrated using samples of real data with continuous outcome and exposure data and several covariates. The sample data set, segments of Stata and R code, and outputs are provided to enable replication of the results.
Conclusion
These methods and tools can be adapted to other situations, including for time-to-event or categorical outcomes, different ways of modelling exposure-outcome curves, and different strategies for covariate adjustment.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2021 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) |
Keywords: | Meta-analysis; individual participant data; continuous variables; fractional polynomials |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) > Leeds Institute of Cardiovascular and Metabolic Medicine (LICAMM) > Clinical & Population Science Dept (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 06 Sep 2021 10:22 |
Last Modified: | 18 Oct 2024 14:36 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.jclinepi.2021.08.033 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:177830 |