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Methods for Estimating Adjusted Risk Ratios
Open accessAbstract
The risk ratio can be a useful statistic for summarizing the results of cross-sectional, cohort, and randomized trial studies. I discuss several methods for estimating adjusted risk ratios and show how they can be executed in Stata, including 1) Mantel–Haenszel and inverse-variance stratified methods; 2) generalized linear regression with a log link and binomial distribution; 3) generalized linear regression with a log link, normal distribution, and robust variance estimator; 4) Poisson regression with a robust variance estimator; 5) Cox proportional hazards regression with a robust variance estimator; 6) standardized risk ratios from logistic, probit, complementary log-log, and log-log regression; and 7) a substitution method. Advantages and drawbacks are noted for some methods.
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Tufanaru, C., Munn, Z., Stephenson, M., & Aromataris, E. (2015) · International Journal of Evidence-Based Healthcare · doi:10.1097/xeb.0000000000000065 · Cited by 1,057
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Worldwide Survey on the Use of Navigation in Spine Surgery
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Sen, S., Potnuru, P. P., Hernandez, N., Goehl, C., Praestholm, C., Sridhar, S., & Nwokolo, O. O. (2024) · JAMA Surgery · doi:10.1001/jamasurg.2024.0111 · Cited by 202
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Metadata
- Authors
- Cummings, P.
- Venue
- The Stata Journal: Promoting communications on statistics and Stata
- Publisher
- SAGE Publications
- Published
- 2009-08
- Volume
- 9
- Issue
- 2
- Pages
- 175-196
- ISSN
- 1536-867X (ISSN-L)
- 1536-8734
- OpenAlex
- W1533121952
- Cited by
- 324
- References
- 55
- FWCI
- 3.28
- Type
- journal article
- Language
- en
- Open access
- bronze
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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