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Multivariate Dose-Response Meta-Analysis: The dosresmeta R Package

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  • Crippa, Alessio
  • Orsini, Nicola

Abstract

An increasing number of quantitative reviews of epidemiological data includes a doseresponse analysis. Aims of this paper are to describe the main aspects of the methodology and to illustrate the novel R package dosresmeta developed for multivariate dose-response meta-analysis of summarized data. Specific topics covered are reconstructing covariances of correlated outcomes; pooling of study-specific trends; flexible modeling of the exposure; testing hypothesis; assessing statistical heterogeneity; and presenting in either a graphical or tabular way the overall dose-response association.

Suggested Citation

  • Crippa, Alessio & Orsini, Nicola, 2016. "Multivariate Dose-Response Meta-Analysis: The dosresmeta R Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 72(c01).
  • Handle: RePEc:jss:jstsof:v:072:c01
    DOI: http://hdl.handle.net/10.18637/jss.v072.c01
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    References listed on IDEAS

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    1. Nicola Orsini & Rino Bellocco & Sander Greenland, 2006. "Generalized least squares for trend estimation of summarized dose–response data," Stata Journal, StataCorp LP, vol. 6(1), pages 40-57, March.
    2. Liu, Qin & Cook, Nancy R. & Bergström, Anna & Hsieh, Chung-Cheng, 2009. "A two-stage hierarchical regression model for meta-analysis of epidemiologic nonlinear dose-response data," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 4157-4167, October.
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