Clinical　trials　frequently　involve　pairwise　comparisons　of　different　treatments　to　evaluate　their　relative　efficacy.　In　this　study,　we　examine　methods　for　conducting　pairwise　tests　of　treatments　with　ordered　categorical　responses.　A　modified　version　of　the　Wilcoxon-Mann-Whitney　test　based　on　a　logistic　regression　model　assuming　proportional　odds　is　a　popular　choice　for　comparing　two　treatments.　This　paper　discusses　the　extension　of　this　test　to　pairwise　comparisons　involving　more　than　two　treatments.　However,　when　the　proportional　odds　assumption　is　not　valid,　the　Wilcoxon-Mann-Whitney-type　test　procedure　cannot　control　the　overall　type　I　error　rate　at　the　prespecified　level　of　significance.　We　therefore　propose　a　better　strategy　in　which　a　latent　normal　model　is　employed.　We　presented　a　simulated　comparative　study　of　power　and　the　overall　type　I　error　rate　to　illustrate　the　superiority　of　the　latent　normal　model.　Examples　are　also　given　for　illustrative　purposes.　Copyright　(c)　2013　John　Wiley　&　Sons,　Ltd.