Accession Number : ADA133416

Title :   Experimental Designs for Quantal Response Models.

Descriptive Note : Final rept. 24 Jun 82-23 Jun 83,

Corporate Author : WISCONSIN UNIV-MADISON DEPT OF STATISTICS

Personal Author(s) : Wu,Chien-Fu Jeff

PDF Url : ADA133416

Report Date : 22 Sep 1983

Pagination or Media Count : 5

Abstract : Three problems have been studied. A new sequential design procedure has been developed for estimating the percentiles of a quantal response curve which describes the probability of response as a function of stimulus level. It is asymptotically fully efficient and distribution-free. For small samples it outperforms the best Robbins-Monro procedure in an extensive empirical study. The percentages of saving range from 25% to 60%. It is shown that, by classifying the outcome of a sensitivity experiment into more than two categories, the parameters in a parametric response curve can be estimated more precisely. The theoretical result is obtained via the Missing Information Principle. The empirical study points out where substantial gains can be achieved. Several procedures for the multiple comparison of all linear contrasts in unbalanced situations are compared both empirically and theoretically. Recommendations for the choice of procedures are given. (Author)

Descriptors :   *Mathematical models, *Experimental design, *Curvature, Stochastic processes, Response, Estimates, Sampling, Parametric analysis, Sensitivity

Subject Categories : Statistics and Probability
      Test Facilities, Equipment and Methods

Distribution Statement : APPROVED FOR PUBLIC RELEASE