CDOoDocuments.StdDocumentDescDocuments.DocumentDescContainers.ViewDescViews.ViewDescStores.StoreDesc@Documents.ModelDescContainers.ModelDescModels.ModelDescStores.ElemDesc TextViews.StdViewDescTextViews.ViewDesc0TextModels.StdModelDescTextModels.ModelDesc:2QTextModels.AttributesDesc*# HERE IS THE WEIBULL REGRESSION MODEL, CARLIN AND HODGES (1999) DATA: model { for(i in 1:nsub[1]) { t1[i] ~ dweib(r, mu1[i])I(t1.cen[i],) mu1[i] <- exp(beta0+beta1*X1[i]+W[1]) } for(i in 1:nsub[2]) { t2[i] ~ dweib(r, mu2[i])I(t2.cen[i],) mu2[i] <- exp(beta0+beta1*X2[i]+W[2]) } for(i in 1:nsub[3]) { t3[i] ~ dweib(r, mu3[i])I(t3.cen[i],) mu3[i] <- exp(beta0+beta1*X3[i]+W[3]) } for(i in 1:nsub[4]) { t4[i] ~ dweib(r, mu4[i])I(t4.cen[i],) mu4[i] <- exp(beta0+beta1*X4[i]+W[4]) } for(i in 1:nsub[5]) { t5[i] ~ dweib(r, mu5[i])I(t5.cen[i],) mu5[i] <- exp(beta0+beta1*X5[i]+W[5]) } for(i in 1:nsub[6]) { t6[i] ~ dweib(r, mu6[i])I(t6.cen[i],) mu6[i] <- exp(beta0+beta1*X6[i]+W[6]) } for(i in 1:nsub[7]) { t7[i] ~ dweib(r, mu7[i])I(t7.cen[i],) mu7[i] <- exp(beta0+beta1*X7[i]+W[7]) } for(i in 1:nsub[8]) { t8[i] ~ dweib(r, mu8[i])I(t8.cen[i],) mu8[i] <- exp(beta0+beta1*X8[i]+W[8]) } for(i in 1:nsub[9]) { t9[i] ~ dweib(r, mu9[i])I(t9.cen[i],) mu9[i] <- exp(beta0+beta1*X9[i]+W[9]) } for(i in 1:nsub[10]) { t10[i] ~ dweib(r, mu10[i])I(t10.cen[i],) mu10[i] <- exp(beta0+beta1*X10[i]+W[10]) } # FIRST, CONSIDER A NONSPATIAL FRAILTY MODEL: for (i in 1:NSITES){ W[i] ~ dnorm(0.0, tau)} r ~ dgamma(.1, .1) tau ~ dgamma(0.01, 0.01); sigmasqu <- 1 / tau; beta0 ~ dnorm(0.0, 0.001) beta1 ~ dnorm(0.0, 0.001) # NEXT, CONSIDER A SPATIAL FRAILTY MODEL: # for(i in 1:NSITES){ # muW[i] <- 0.0 # H[i,i] <- sigmasqu # for (j in i+1:NSITES) { # H[i,j] <- sigmasqu*exp(-phi*d[i,j]) # H[j,i] <- H[i,j] # } # } # phi ~ dgamma(3, 0.1) # W[1:NSITES] ~ dmnorm(muW[], OmegaW[,]) # for (i in 1:NSITES) { # for (j in 1:NSITES) { # OmegaW[i,j] <- inverse(H[,],i,j) # } # } } # Initial values # Nonspatial: list(r=1.0, tau=10.0, beta1=1.0, beta0=-10.0, W=c(0,0,0,0,0,0,0,0,0,0)) # Spatial: #list(r=1.0, tau=10.0, phi=30.0, beta1=0.0, beta0=0.0) # Here are the survival data: list(NSITES=10, nsub=c(4,2,1,10,8,18,6,13,4,3), t1=c(NA,248,NA,344), t1.cen=c(74,0,272,0), t2=c(NA,NA), t2.cen=c(4,156), t3=c(NA), t3.cen=c(100), t4=c(NA,64,88,NA,NA,NA,NA,NA,NA,NA), t4.cen=c(20,0,0,148,162,184,188,198,382,436), t5=c(NA,NA,82,NA,NA,214,NA,262), t5.cen=c(50,64,0,186,214,0,228,0), t6=c(6,NA,76,80,202,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,162), t6.cen=c(0,16,0,0,0,258,268,368,380,424,428,436,22,22,74,88,148,0), t7=c(NA,NA,102,NA,NA,NA), t7.cen=c(32,64,0,162,182,364), t8=c(8,NA,40,NA,NA,NA,NA,276,NA,366,NA,NA,NA), t8.cen=c(0,16,0,120,168,174,268,0,286,0,396,466,468), t9=c(NA,NA,NA,254), t9.cen=c(18,36,160,0), t10=c(NA,NA,NA), t10.cen=c(28,70,106), X1=c(1,2,1,2), X2=c(2,1), X3=c(2), X4=c(2,2,2,2,1,1,1,1,1,1), X5=c(1,2,2,1,1,1,2,2), X6=c(1,2,1,2,2,1,1,2,1,1,2,2,2,1,1,1,1,2), X7=c(2,1,1,2,2,1), X8=c(2,2,2,1,1,2,1,2,1,1,2,2,1), X9=c(1,1,2,2), X10=c(1,1,2)) # Here are the location data (load only for spatial model:) d[,1] d[,2] d[,3] d[,4] d[,5] d[,6] d[,7] d[,8] d[,9] d[,10] 0.0000 0.4562 0.0806 1.0000 0.9503 0.1872 0.2918 0.1126 0.0319 0.7062 0.4562 0.0000 0.3758 0.7492 0.8028 0.3662 0.1652 0.3484 0.4247 0.4003 0.0806 0.3758 0.0000 0.9492 0.9151 0.1538 0.2112 0.0373 0.0489 0.6425 1.0000 0.7492 0.9492 0.0000 0.2085 0.8135 0.8323 0.9496 0.9821 0.3489 0.9503 0.8028 0.9151 0.2085 0.0000 0.7656 0.8452 0.9242 0.9387 0.4315 0.1872 0.3662 0.1538 0.8135 0.7656 0.0000 0.2328 0.1733 0.1732 0.5310 0.2918 0.1652 0.2112 0.8323 0.8452 0.2328 0.0000 0.1833 0.2601 0.4948 0.1126 0.3484 0.0373 0.9496 0.9242 0.1733 0.1833 0.0000 0.0809 0.6350 0.0319 0.4247 0.0489 0.9821 0.9387 0.1732 0.2601 0.0809 0.0000 0.6827 0.7062 0.4003 0.6425 0.3489 0.4315 0.5310 0.4948 0.6350 0.6827 0.0000 TextControllers.StdCtrlDescTextControllers.ControllerDescContainers.ControllerDescControllers.ControllerDesc TextRulers.StdRulerDescTextRulers.RulerDescTextRulers.StdStyleDescTextRulers.StyleDescZTextRulers.AttributesDesc$0ZGo * <[ @Documents.ControllerDesc v x k{