Unconstrained Covariate Adjustment in CTA
Paul R. Yarnold, Ph.D. and Robert C. Soltysik, M.S.
Optimal Data Analysis, LLC
In traditional statistical covariate analysis it is common practice to force entry of the covariate into the model first, to eliminate the effect of the covariate (i.e., “equate the groups”) on the dependent measure. In contrast, in CTA the covariate is treated as an ordinary attribute which must compete with other eligible attributes for selection into the model based on operator-specified options. This paper illustrates optimal covariate analysis using an application involving predicting patient in-hospital mortality via CTA.
