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Abstract Direct effects in mediation analysis quantify the effect of an exposure on an outcome not mediated by a certain intermediate. When estimating direct effects through measured data, misclassification may occur in the outcomes, exposures, and mediators. In mediation analysis, any such...
Persistent link: https://www.econbiz.de/10014610888
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To develop and validate a general method (called regression risk analysis) to estimate adjusted risk measures from logistic and other nonlinear multiple regression models. We show how to estimate standard errors for these estimates. These measures could supplant various approximations (e.g.,...
Persistent link: https://www.econbiz.de/10009477267
Matching is occasionally used in cohort studies; examples include studies of twins and some studies of traffic crashes. Analysis of matched cohort data is not discussed in many textbooks or articles and is not mentioned in the Stata manuals. Risk ratios can be estimated using matched-pair cohort...
Persistent link: https://www.econbiz.de/10005583270
In this article, we explain 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 postestimation command, adjrr, that calculates adjusted risk ratios and adjusted...
Persistent link: https://www.econbiz.de/10010691932
Optimal allocation designs for the allocation proportion are obtained in the present paper for a two-treatment situation, in a completely correlated setup where the sum of the responses no longer follows a binomial distribution. We consider treatment difference and odds ratio to find the optimal...
Persistent link: https://www.econbiz.de/10011039852
In a two-sample clinical trial, a fixed proportion of true-and-surrogate and the remaining only-surrogate responses are observed. We quantify the increase in efficiency to compare the treatments as a linear function of the proportion of available true responses.
Persistent link: https://www.econbiz.de/10011115956
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, in- cluding 1) Mantel – Haenszel and inverse-variance...
Persistent link: https://www.econbiz.de/10004964309
Persistent link: https://www.econbiz.de/10012699311
Abstract Standard measures of effect, including the risk ratio, the odds ratio, and the risk difference, are associated with a number of well-described shortcomings, and no consensus exists about the conditions under which investigators should choose one effect measure over another. In this...
Persistent link: https://www.econbiz.de/10014590629