Accession Number : AD0759733
Title : Optimal Designs and Large Sample Tests for Linear Hypotheses.
Descriptive Note : Research rept.,
Corporate Author : VIRGINIA POLYTECHNIC INST AND STATE UNIV BLACKSBURG DEPT OF STATISTICS
Personal Author(s) : Jensen,Donald R. ; Mayer,Lawrence S. ; Myers,Raymond H.
Report Date : 01 MAY 1973
Pagination or Media Count : 29
Abstract : The study investigates the appropriateness of normal-theory inference for linear models having non-Gaussian errors. It is shown that bounds on the error of the Gaussian approximation depend on the design; the optimal designs are characterized and shown to be orthogonal. Bounds on the actual probabilities associated with Scheffe's projections, and with Dunnett's procedure for comparing several treatments with a control, are given in terms of their normal-theory approximations. (Author)
Descriptors : (*MULTIVARIATE ANALYSIS, EXPERIMENTAL DESIGN), SAMPLING, PROBABILITY DENSITY FUNCTIONS, MATRICES(MATHEMATICS), RANDOM VARIABLES, THEOREMS
Subject Categories : Statistics and Probability
Distribution Statement : APPROVED FOR PUBLIC RELEASE