Calculation of polychotomous logistic regression parameters using individualized regressions

Abstract

The use of individualized logistic regression, in which a series of separate simple logistic regression analyses are performed as a replacement for polychotomous logistic regression, is studied. The asymptotic relative efficiencies of the individual parameter estimates are observed to be generally high, as are the efficiencies of predicted probability estimates and, to a somewhat lesser extent, joint tests of parameters from different regressions.