Accession Number : AD0675558

Title :   LINEAR MODELS AND ANALYSIS OF VARIANCE RESEARCH PROCEDURES,

Corporate Author : IOWA STATE UNIV OF SCIENCE AND TECHNOLOGY AMES

Personal Author(s) : Zyskind,G. ; Kempthorne,O. ; Martin,F. B. ; Carney,E. J. ; West,E. N.

Report Date : JUL 1968

Pagination or Media Count : 188

Abstract : Research on some related linear model theory and analysis of variance procedures is described. Chapter I is introductory, giving a general outline of topics described in the report. Chapter II presents a formulation of aspects of best and simple least squares linear estimation in linear models with arbitrary, possibly singular, covariance structure. Chapter III develops a generalization of the famed Gauss-Markoff theorem, applying to situations including a singular variance-covariance structure of the observations. Chapter IV deals with simple combination of information in linear models originating from uncorrelated distinct sources of information. Chapter V deals with some formulations of sampling from balanced complete experimental structures, and with theoretical and computational aspects arising in the calculation of variances of variance components. Chapter VI presents results of a Monte Carlo investigation of significance levels generated by the Behrens-Fisher fiducial procedure and by the Welch Aspin procedure. Chapter VII presents a brief discussion of certain non-parametric test procedures based upon ranks and, in particular, points up the problems arising from the inevitable grouping error of measurement. (Author)

Descriptors :   (*ANALYSIS OF VARIANCE, MATHEMATICAL MODELS), LINEAR SYSTEMS, LEAST SQUARES METHOD, DECISION THEORY, SAMPLING, MONTE CARLO METHOD, VECTOR SPACES, STATISTICAL DISTRIBUTIONS, STATISTICAL TESTS, CORRELATION TECHNIQUES, COMBINATORIAL ANALYSIS, THEOREMS

Subject Categories : Statistics and Probability

Distribution Statement : APPROVED FOR PUBLIC RELEASE