%0 Journal Article %1 williamson1999geecat %A Williamson, J M %A Lipsitz, S R %A Kim, K M %D 1999 %J Comput Methods Programs Biomed %K CorrelatedData LongitudinalDataAnalysis gee sas statistics %N 1 %P 25-34 %T GEECAT and GEEGOR: computer programs for the analysis of correlated categorical response data %U https://www.ncbi.nlm.nih.gov/pubmed/10195644 %V 58 %X GEECAT and GEEGOR are two user-friendly SAS macros for the analysis of clustered, correlated categorical response data. Both programs implement methodology which extend the generalized estimating equation (GEE) approach of Liang and Zeger (Biometrika 73 (1986) 13-22). GEECAT and GEEGOR both use a first set of estimating equations to model the marginal response. With GEECAT, either correlated nominal or ordered categorical response data can be analyzed. The program GEEGOR employs a second set of estimating equations to model the association of ordered categorical responses within a cluster using the global odds ratio as a measure of association. The programs run on both mainframe computers and microcomputers. Examples are provided to illustrate the features of both programs.

@article{williamson1999geecat, abstract = {GEECAT and GEEGOR are two user-friendly SAS macros for the analysis of clustered, correlated categorical response data. Both programs implement methodology which extend the generalized estimating equation (GEE) approach of Liang and Zeger (Biometrika 73 (1986) 13-22). GEECAT and GEEGOR both use a first set of estimating equations to model the marginal response. With GEECAT, either correlated nominal or ordered categorical response data can be analyzed. The program GEEGOR employs a second set of estimating equations to model the association of ordered categorical responses within a cluster using the global odds ratio as a measure of association. The programs run on both mainframe computers and microcomputers. Examples are provided to illustrate the features of both programs.}, added-at = {2018-09-21T10:12:18.000+0200}, author = {Williamson, J M and Lipsitz, S R and Kim, K M}, biburl = {https://www.bibsonomy.org/bibtex/2373c214afe64d933ca784419f95dd766/jkd}, description = {GEECAT and GEEGOR: computer programs for the analysis of correlated categorical response data. - PubMed - NCBI}, interhash = {25cc266c9317068c9735655cf735bd65}, intrahash = {373c214afe64d933ca784419f95dd766}, journal = {Comput Methods Programs Biomed}, keywords = {CorrelatedData LongitudinalDataAnalysis gee sas statistics}, month = jan, number = 1, pages = {25-34}, pmid = {10195644}, timestamp = {2018-10-03T05:30:04.000+0200}, title = {GEECAT and GEEGOR: computer programs for the analysis of correlated categorical response data}, url = {https://www.ncbi.nlm.nih.gov/pubmed/10195644}, volume = 58, year = 1999 }