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The Stata Journal
Volume 6 Number 1: pp. 40-57



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

Nicola Orsini
Karolinska Institutet
Stockholm, Sweden
nicola.orsini@ki.se
Rino Bellocco
Karolinska Institutet
Stockholm, Sweden
Sander Greenland
UCLA School of Public Health
Los Angeles, CA
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.
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