Michael Hills () David Clayton () (BSU, Cambridge)
Abstract
At the UK Stata User's Group meeting in 2000, we presented a series of linked commands which made it possible to declare exposure, stratifying and confounding variables, and to combine this information with Stata estimation commands such as regress, logistic, poisson, stcox, xtpois, etc., to produce maximum likelihood estimates of stratum-specific exposure effects, possibly controlled for other confounders. Essentially, the idea was that the estimation techniques should be ML, but the output should be closer to Mantel?Haenszel than to the traditional table of main effects and interactions. In this presentation, we demonstrate the use of a Graphical Interface as an alternative way of declaring the information which will guide the analysis. The GI was prepared using Stata's windowing commands. We are not advocating the use of GI's in place of the command line as a general strategy, only where the information to be passed to a command is complex.
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