Generalized least squares for trend estimation of summarized dose–response data

Nicola Orsini, Rino Bellocco and Sander Greenland
Additional contact information
Rino Bellocco: Karolinska Institutet
Sander Greenland: UCLA School of Public Health

Stata Journal, 2006, vol. 6, issue 1, pages 40-57

Abstract: This paper presents a command, glst, for trend estimation across different exposure levels for either single or multiple summarized case-control, incidence-rate, and cumulative incidence data. This approach is based on constructing an approximate covariance estimate for the log relative risks and estimating a corrected linear trend using generalized least squares. For trend analysis of multiple studies, glst can estimate fixed- and random-effects metaregression models. Copyright 2006 by StataCorp LP.

Keywords: glst; dose–response data; generalized least squares; trend; meta-analysis; metaregression (search for similar items in EconPapers)
Date: 2006

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Persistent link: http://EconPapers.repec.org/RePEc:tsj:stataj:v:6:y:2006:i:1:p:40-57

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