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Weighted mixed-effects dose–response models for tables of correlated contrasts

Author

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  • Nicola Orsini

    (Karolinska Institutet)

Abstract

Recognizing a dose–response pattern based on heterogeneous tables of contrasts is hard. Specification of a statistical model that can consider the possible dose–response data-generating mechanism, including its variation across studies, is crucial for statistical inference. The aim of this article is to increase the un- derstanding of mixed-effects dose–response models suitable for tables of correlated estimates. One can use the command drmeta with additive (mean difference) and multiplicative (odds ratios, hazard ratios) measures of association. The postes- timation command drmeta graph greatly facilitates the visualization of predicted average and study-specific dose–response relationships. I illustrate applications of the drmeta command with regression splines in experimental and observational data based on nonlinear and random-effects data-generation mechanisms that can be encountered in health-related sciences.

Suggested Citation

  • Nicola Orsini, 2021. "Weighted mixed-effects dose–response models for tables of correlated contrasts," Stata Journal, StataCorp LP, vol. 21(2), pages 320-347, June.
    • Handle: RePEc:tsj:stataj:v:21:y:2021:i:2:p:320-347
    DOI: 10.1177/1536867X211025798
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    Cited by:

    1. Narmeen Mallah & Nicola Orsini & Adolfo Figueiras & Bahi Takkouche, 2022. "Income level and antibiotic misuse: a systematic review and dose–response meta-analysis," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 23(6), pages 1015-1035, August.

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