Abstract
A-optimal design measures are obtained for some second-order polyno-micd regression models over cubic experimental regions using a method involving minimization of convex univariate functions. Performance of these design measures under model variation is examined. A-optimal design measures among the central composite type are also derived. The efficiency of these and some integer central composite designs requiring a practicable number of trials is investigated.