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Generalized Least Squares for Trend Estimation of Summarized Dose–response Data
Open accessAbstract
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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Metadata
- Authors
- Orsini, N., Bellocco, R., & Greenland, S.
- Venue
- The Stata Journal: Promoting communications on statistics and Stata
- Publisher
- SAGE Publications
- Published
- 2006-02
- Volume
- 6
- Issue
- 1
- Pages
- 40-57
- ISSN
- 1536-867X (ISSN-L)
- 1536-8734
- OpenAlex
- W1605393132
- Cited by
- 1,241
- References
- 3
- FWCI
- 12.81
- Type
- journal article
- Language
- en
- Open access
- bronze
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