In　clinical　studies,　multiple　comparisons　of　several　treatments　to　a　control　with　ordered　categorical　responses　are　often　encountered.　A　popular　statistical　approach　to　analyzing　the　data　is　to　use　the　logistic　regression　model　with　the　proportional　odds　assumption.　As　discussed　in　several　recent　research　papers,　if　the　proportional　odds　assumption　fails　to　hold,　the　undesirable　consequence　of　an　inflated　familywise　type　I　error　rate　may　affect　the　validity　of　the　clinical　findings.　To　remedy　the　problem,　a　more　flexible　approach　that　uses　the　latent　normal　model　with　single-step　and　stepwise　testing　procedures　has　been　recently　proposed.　In　this　paper,　we　introduce　a　step-up　procedure　that　uses　the　correlation　structure　of　test　statistics　under　the　latent　normal　model.　A　simulation　study　demonstrates　the　superiority　of　the　proposed　procedure　to　all　existing　testing　procedures.　Based　on　the　proposed　step-up　procedure,　we　derive　an　algorithm　that　enables　the　determination　of　the　total　sample　size　and　the　sample　size　allocation　scheme　with　a　pre-determined　level　of　test　power　before　the　onset　of　a　clinical　trial.　A　clinical　example　is　presented　to　illustrate　our　proposed　method.　Copyright　(c)　2014　John　Wiley　&　Sons,　Ltd.