HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS		QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

This Article Full Text (PDF) Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Harvey, W. R. Search for Related Content PubMed Articles by Harvey, W. R.

Least-Squares Analysis of Discrete Data¹

The Ohio State University, Columbus 43210

Abstract

There are two important advantages of using general least-squares procedures to analyze discrete data. First is the ready availability of general least-squares computer programs. Second is the greater flexibility in the models which may be used when analyzed under least-squares procedures rather than by other methods. For example, one can easily complete covariance and even multiple covariance analyses under the least-squares procedures. Also, analyses may be completed under complex mixed models, and estimates of variance components for discrete characters, as well as covariance components between discrete and continuous traits, may be obtained. However, this summary would not be complete without a word of caution regarding tests of significance. Clearly, estimates of "treatment" effects and least-squares means obtained from an analysis of discrete data by least-squares procedures are unbiased. The accuracy of tests of significance depends largely on whether adequate numbers are available for the estimation of treatment or subclass means. In general, for binomial data, if nµ and n(lµ) are greater than or equal to 5 the tests of significance from a least-squares analysis will be accurate enough for practical purposes, where µ is the probability of "success" and n is the sample size.

¹ Invitational paper presented at a Symp. on "Statistical Analysis of Categorical Data in Animal Research," Annu. Meet, of ASAS, Cornell Univ., Ithaca, NY, July 28,1980.

This article has been cited by other articles:

				J. E. Winkler Stirm and N. R. St-Pierre Identification and Characterization of Location Decision Factors for Relocating Dairy Farms J Dairy Sci, November 1, 2003; 86(11): 3473 - 3487. [Abstract] [Full Text] [PDF]

				M. Hansen, P. Madsen, J. Jensen, J. Pedersen, and L. G. Christensen Genetic Parameters of Postnatal Mortality in Danish Holstein Calves J Dairy Sci, May 1, 2003; 86(5): 1807 - 1817. [Abstract] [Full Text] [PDF]