Computing adjusted risk ratios and risk differences in Stata
Computing adjusted risk ratios and risk differences in Stata
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DOI：
10.1177/1536867x1301300304
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发表时间：
2013-01-01
期刊：
影响因子：
4.8
通讯作者：
Kleinman, Lawrence C.
中科院分区：
文献类型：
--
作者：
Norton, Edward C.;Miller, Morgen M.;Kleinman, Lawrence C.
在本文中，我们将解释在报告logit、probit和相关非线性模型的结果时，如何计算调整后的风险比率和风险差异。在Stata的保证金命令的基础上，我们创建了一个新的后估计命令，adjrr，它在运行logit或probit模型后计算调整后的风险比率和调整后的风险差异，这些模型具有二元、多项或有序的结果。Adjrr报告点估计、δ法标准误差和95%置信区间，并可以为感兴趣的变量的特定值计算这些。它自动调整复杂的调查设计，如在拟合模型。来自医疗支出小组调查和国民健康和营养检查调查的数据被用来说明该命令的多种应用。
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 risk differences after running a logit or probit model with a binary, a multinomial, or an ordered outcome. adjrr reports the point estimates, delta-method standard errors, and 95% confidence intervals and can compute these for specific values of the variable of interest. It automatically adjusts for complex survey design as in the fit model. Data from the Medical Expenditure Panel Survey and the National Health and Nutrition Examination Survey are used to illustrate multiple applications of the command.