Abstract
This chapter presents an overview on meta-analysis (MA) intended for public health researchers to understand and to apply the methods of MA. Emphasis is focused on classical statistical methods for estimation of the parameters of interest in MA as well as recent development in research in MA. Specifically, univariate and multivariate fixed- and random-effects MAs, as well as meta-regression are discussed. All methods are illustrated by examples of published MA in public health research. We demonstrate how these approaches can be implemented using software packages in R.
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Appendix
Appendix
We performed all our analyses in R using the mvmeta package. In this appendix we provide the R code written for the meta-analysis and meta-regression in Example 1.
###R code for fixed effects UMA:
where var.PD stands for the within-study variance of PD.
###R code for random effects UMA:
###R code for fixed effects BMA:
where cov.PD.AL stands for the within-study covariance of PD and AL.
###R code for random effects BMA:
###R code for fixed effects univariate MR:
###R code for random effects univariate MR:
###R code for fixed effects bivariate MR:
###R code for random effects bivariate MR:
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Ma, Y., Zhang, W., Chen, DG. (2015). Meta-Analytic Methods for Public Health Research. In: Chen, DG., Wilson, J. (eds) Innovative Statistical Methods for Public Health Data. ICSA Book Series in Statistics. Springer, Cham. https://doi.org/10.1007/978-3-319-18536-1_15
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DOI: https://doi.org/10.1007/978-3-319-18536-1_15
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