Thesis (Ph. D.)--University of Missouri-Columbia, 1996. / Typescript. Vita. Includes bibliographical references (leaves 116-121). Also available on the Internet.

Thesis (Ph. D.)--University of Missouri-Columbia, 1996. / Typescript. Vita. Includes bibliographical references (leaves 116-121). Also available on the Internet.

Box-Behnken designs are used to estimate parameters in a second-order response surface model (Box and Behnken, 1960). These designs are formed by combining ideas from incomplete block designs (BIBD or PBIBD) and factorial experiments, specifically 2^k full or 2^k-1 fractional factorials. In this dissertation, a more general mathematical formulation of the Box-Behnken method is provided, a general expression for the coefficient matrix in the least squares analysis for estimating the parameters in the second order model is derived, and the properties of Box-Behnken designs with respect to the estimability of all parameters in a second-order model are investigated when 2^kfull factorials are used. The results show that for all pure quadratic coefficients to be estimable, the PBIB(m) design has to be chosen such that its incidence matrix is of full rank, and for all mixed quadratic coefficients to be estimable the PBIB(m) design has to be chosen such that the parameters λ₁, λ₂, ...,λ_m are all greater than zero. In order to reduce the number of experimental points the use of 2^k-1 fractional factorials instead of 2^k full factorials is being considered. Of particular interest and importance are separate considerations of fractions of resolutions III, IV, and V. The construction of Box-Behnken designs using such fractions is described and the properties of the designs concerning estimability of regression coefficients are investigated. Using designs obtained from resolution V factorials have the same properties as those using full factorials. Resolutions III and IV designs may lead to non-estimability of certain coefficients and to correlated estimators. The final topic is concerned with Box-Behnken designs in which treatments are applied to experimental units sequentially in time or space and in which there may exist a linear trend effect. For this situation, one wants to find appropriate run orders for obtaining a linear trend-free Box-Behnken design to remove a linear trend effect so that a simple technique, analysis of variance, instead of a more complicated technique, analysis of covariance, to remove a linear trend effect can be used. Construction methods for linear trend-free Box-Behnken designs are introduced for different values of block size (for the underlying PBIB design) k. For k= 2 or 3, it may not always be possible to find linear trend-free Box-Behnken designs. However, for k ≥ 4 linear trend-free Box-Behnken designs can always be constructed. / Ph. D.

A method is presented for analysing a 2 x 2 factorial experiment in which the data consist cf relative rankings in pairwise comparisons. Maximum likelihood estimates are developed for the ratings of the various levels of each factor und for the treatment combinations. Likelihood ratio tests of the most important hypotheses likely to arise are derived in detail. The large sample approximations are used. In addition, the method is presented in a manner such that tests of other hypotheses in which the experimenter might be interested can easily be derived. The equations for the analysis of a factorial design of arbitrary size are presented, It can be seen, however, that the complexity of these equations render an attempt at their solution impractical in most cases and more work must be done if a useful method of analysing experiments of this, type is to be found. / Master of Science

Robert J. Taylor and Herbert A. David developed a new experimental approach in the screening of prospective drugs to be used in the treatment of cancer. The procedure is a sequential one, where the allocation of patients to drugs is based upon the performance of the drugs in immediately previous periods. Taylor further developed a computer program to study the effectiveness of the procedure by means of simulated trials. The purpose of this paper has been to study the sequential allocation procedure further by means of simulation in the form of a factorial experiment. Of primary concern has been the behavior of different weighting functions operating under varying experimental conditions. Response variables have been studied as a means for evaluating the effectiveness of the procedure. The results of this experiment are comparable with the findings originally presented by Taylor and David. / Master of Science