A COMPARISON OF SOME METHODS TO ANALYZE REPEATED MEASURES ORDINAL CATEGORICAL DATA

Yaobing Sui, Walter W. Stroup
2001 Conference on Applied Statistics in Agriculture  
Recent advances in statistical software made possible by the rapid development of computer technology in the past decade have made many new procedures available to data analysts. We focus in this paper on methods for ordinal categorical data with repeated measures that can be implemented using SAS. These procedures are illustrated using data from an animal health experiment. The responses, measured as severity of symptoms on an ordinal scale, are recorded for test animals over time. The
more » ... r time. The experiment was designed to estimate treatment and time effects on the severity of symptoms. The data were analyzed with various approaches using PROC MIXED, PROC NLMIXED, PROC GENMOD, and the GLIMMIX macro. In this paper, we compare the strengths and weaknesses of these different methods. ( 7ti'k (1-7t n )] where D=diag J J , and n ijk is the number of Bernoulli trials observed on the ijk th n ijk treatmentxblockxweek combination. The form of D given here is specific to the binomial distribution. In general, D a diagonal matrix whose elements are the variance functions with for each treatmentxblockxweek combination. P is a working correlation matrix. Working correlation matrices are not true correlation matrices, but their structure follows common correlated error
doi:10.4148/2475-7772.1219 fatcat:t3jhjh7rzbbc5hbebvyzj4goqi