Methods for Estimating Adjusted Risk Ratios
نویسندگان
چکیده
منابع مشابه
Estimating model-adjusted risks, risk differences, and risk ratios from complex survey data.
There is increasing interest in estimating and drawing inferences about risk or prevalence ratios and differences instead of odds ratios in the regression setting. Recent publications have shown how the GENMOD procedure in SAS (SAS Institute Inc., Cary, North Carolina) can be used to estimate these parameters in non-population-based studies. In this paper, the authors show how model-adjusted ri...
متن کاملPractice of Epidemiology Estimating Model-Adjusted Risks, Risk Differences, and Risk Ratios From Complex Survey Data
There is increasing interest in estimating and drawing inferences about risk or prevalence ratios and differences instead of odds ratios in the regression setting. Recent publications have shown how the GENMOD procedure in SAS (SAS Institute Inc., Cary, North Carolina) can be used to estimate these parameters in non-population-based studies. In this paper, the authors show how model-adjusted ri...
متن کاملComputing adjusted risk ratios and risk differences in Stata
This paper explains how to calculate adjusted risk ratios and risk differences when reporting results from logit, probit, and related nonlinear models. Building on Stata’s margins command, we create a new post-estimation command adjrr that calculates adjusted risk ratios (ARR) and adjusted risk differences (ARD) after running logit or probit models with either binary, multinomial, or ordered ou...
متن کاملMethods for estimating prevalence ratios in cross-sectional studies.
OBJECTIVE To empirically compare the Cox, log-binomial, Poisson and logistic regressions to obtain estimates of prevalence ratios (PR) in cross-sectional studies. METHODS Data from a population-based cross-sectional epidemiological study (n = 2072) on elderly people in Sao Paulo (Southeastern Brazil), conducted between May 2003 and April 2005, were used. Diagnoses of dementia, possible cases ...
متن کاملA comparison of two methods for estimating prevalence ratios
BACKGROUND It is usually preferable to model and estimate prevalence ratios instead of odds ratios in cross-sectional studies when diseases or injuries are not rare. Problems with existing methods of modeling prevalence ratios include lack of convergence, overestimated standard errors, and extrapolation of simple univariate formulas to multivariable models. We compare two of the newer methods u...
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ژورنال
عنوان ژورنال: The Stata Journal: Promoting communications on statistics and Stata
سال: 2009
ISSN: 1536-867X,1536-8734
DOI: 10.1177/1536867x0900900201