CDOoDocuments.StdDocumentDescDocuments.DocumentDescContainers.ViewDescViews.ViewDescStores.StoreDesc Documents.ModelDescContainers.ModelDescModels.ModelDescStores.ElemDescV N TextViews.StdViewDescTextViews.ViewDescTextModels.StdModelDescTextModels.ModelDescTextModels.AttributesDesc1$Courier New! $Courier New+* #------------------------------------------------------------------------------------------------------------------------------ Version 2 (using CR/STZ dummies) #------------------------------------------------------------------------------------------------------------------------------ model{ for (i in 1:n){ Test[i] <- equals( drug[i], 2 ) # CR dummy for test treatment #Test[i] <- equals( drug[i], 2 )-equals( drug[i], 1 ) # STZ dummy # model likelihood y[i] ~ dnorm( mu[i], tau ) mu[i] <- beta0+ alpha2*Test[i] + beta1*log(dose[i]) } # rho <- exp( alpha2/beta1 ) # relative potency in CR #rho <- exp( 2*alpha2/beta1 ) # relative potency in stz # potency estimate potency <- rho * 1.2 # # prior distributions beta0 ~ dnorm( 0.0, 0.001) # constant for standard treatment alpha2 ~ dnorm( 0.0, 0.001) # effect of test treatment beta1 ~ dnorm( 0.0, 0.001) # slope tau ~ dgamma( 0.001, 0.001) # precision of regression model s <- 1/sqrt(tau) # standard error of regression } INITS list( beta0=0, beta1=0, alpha2=0, tau=1 ) DATA (LIST) list( n=24, y=c(68.8, 67.6, 68.1, 67.6, 69.0, 67.9, 68.6, 68.3, 61.4, 59.8, 62.3, 60.6, 60.9, 60.3, 61.6, 61.8, 53.5, 51.9, 53.6, 52.2, 53.8, 54.9, 54.1, 54.2), dose=c(0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.025, 0.050, 0.050, 0.050, 0.050, 0.050, 0.050, 0.050, 0.050, 0.100, 0.100, 0.100, 0.100, 0.100, 0.100, 0.100, 0.100), drug=c(1,1,1,1,2,2,2,2, 1,1,1,1,2,2,2,2, 1,1,1,1,2,2,2,2) ) TextControllers.StdCtrlDescTextControllers.ControllerDescContainers.ControllerDescControllers.ControllerDesc TextRulers.StdRulerDescTextRulers.RulerDescTextRulers.StdStyleDescTextRulers.StyleDescZTextRulers.AttributesDesc$ ZGo * ,[ @Documents.ControllerDesc t]s ' `h*