The　response　variable　in　clinical　studies　is　frequently　ordinal.　In　the　comparison　of　treatment　efficacies,　the　latent　Weibull　model　has　been　shown　to　be　a　powerful　tool　that　is　appropriate　for　testing　even　when　the　data　are　highly　skewed,　a　condition　under　which　the　traditional　proportional　odds　model　may　be　unsuitable　owing　to　the　possible　inflation　of　the　type-I　error　rate.　A　response-adaptive　treatment　randomization　scheme　based　on　the　latent　Weibull　model　has　recently　been　proposed　to　allow　more　patients　to　receive　the　better　treatment　while　maintaining　competitive　test　power.　Nevertheless,　the　proposed　procedure　has　been　restricted　to　the　comparison　of　two　treatments.　This　paper　generalizes　the　aforementioned　idea　to　include　trials　with　multiple　treatments.　Statistical　procedures　for　pairwise　comparisons　and　multiple　comparisons　with　a　control　are　discussed.　Furthermore,　a　simulation　study　is　performed　to　illustrate　the　superiority　of　the　proposed　method.　The　practical　benefits　of　the　suggested　procedures　are　demonstrated　through　the　redesign　of　two　clinical　trials.