無法計算子表達尖齒

Question

我有點新尖齒，和我一直在貨架我的大腦試圖看到我在做什麼錯我的代碼，這是給這個錯誤信息：

「無法計算precd'的子集表達式。

我附加了我的代碼，其中也有編碼的數據。我會很感激所有我能得到的幫助。

nS=number of studies, 
r=number of events, 
n=sample size, 
tau.sq=heterogeneity, 
na=number of arms, 
sw='correction' for multi-arm trials. 

Model<- function(){ 
for(i in 1:nS) { 
    w[i,1]<- 0 
    theta[i,t[i,1]]<- 0 

for (k in 1:na[i]) {r[i,t[i,k]] ~ dbin(p[i,t[i,k]],n[i,t[i,k]])}                 
logit(p[i,t[i,1]])<- u[i]       
for (k in 2:na[i]) { 
    logit(p[i,t[i,k]])<- u[i] + theta[i,t[i,k]] 

    theta[i,t[i,k]] ~ dnorm(md[i,t[i,k]],precd[i,t[i,k]]) 

    md[i,t[i,k]]<- mean[i,k] + sw[i,k]         
    w[i,k]<- (theta[i,t[i,k]] - mean[i,k])   
    sw[i,k]<- sum(w[i,1:k-1])/(k-1) 
    precd[i,t[i,k]]<- prec*2*(k-1)/k 

    mean[i,k] <-d[t[i,k]] - d[t[i,1]] 

}} 

先驗爲基本參數

從這一點結果

for (i in 1:nS) {u[i] ~ dnorm(0,.01)} 

tau ~ dnorm(0,.01)          
prec<- 1/pow(tau,2) 
tau.sq<- pow(tau,2) 

d[ref] <- 0 
for(k in 1:(ref-1)) {d[k] ~ dnorm(0,.01)} 
for(k in (ref+1):nT) {d[k] ~ dnorm(0,.01)} 

保藏中心的治療

for(i in 1:(nT-1)) { 
for (j in (i+1):nT) { 
    OR[j,i]<- exp(d[j] - d[i]) 
    LOR[j,i]<- d[j] - d[i]}} 

for(j in 1:(ref-1)){ORref[j]<- exp(d[j] - d[ref])} 
for(j in (ref+1):nT) {ORref[j]<- exp(d[j] - d[ref])} 

排名

for(k in 1:nT) { 
order[k]<- rank(d[],k) 
most.effective[k]<-equals(order[k],1) 
for(j in 1:nT) {effectiveness[k,j]<- equals(order[k],j) 
cumeffectiveness[k,j]<- sum(effectiveness[k,1:j])}}  

for(k in 1:nT) { 
SUCRA[k]<- sum(cumeffectiveness[k,1:(nT-1)]) /(nT-1) 
} 

for(i in 1:nS) { 
for (k in 1:na[i]) {    
    Darm[i,k]<- -2*(r[i,t[i,k]] *log(n[i,t[i,k]]*p[i,t[i,k]]/ 
r[i,t[i,k]])+(n[i,t[i,k]] - r[i,t[i,k]])*log((n[i,t[i,k]]- 
n[i,t[i,k]]* p[i,t[i,k]])/(n[i,t[i,k]]- r[i,t[i,k]])))} 
D[i]<- sum(Darm[i,1:na[i]])} 
D.bar<- sum(D[]) 
} 

的數據被編碼下面

library(R2jags) 
library(mcmc) 
setwd("PATH-NAME") 
# ******************************************************* 
# Data are coded below: 
# BA -1 
# BMS -2 *** REFERENCE 
# DCB -3 
# EES -4 
# PES -5 
# ROTA -6 
# SES -7 
# VBT -8 
# ******************************************************* 
t_RCT = structure(.Data=c(1,6,NA, 
          1,6,NA, 
          1,2,NA, 
          1,2,NA, 
          2,6,NA, 
          1,2,NA, 
          1,8,NA, 
          1,8,NA, 
          1,8,NA, 
          5,8,NA, 
          5,8,NA, 
          1,5,7, 
          1,7,NA, 
          7,8,NA, 
          7,8,NA, 
          5,7,NA, 
          1,7,NA, 
          1,7,NA, 
          4,7,NA, 
          3,4,NA, 
          3,4,NA, 
          1,3,NA, 
          3,5,NA, 
          1,3,NA, 
          1,3,NA, 
          1,3,NA, 
          1,3,5, 
          3,5,NA), .Dim=c(28,3))      

na_RCT <- c(2,2,2,2,2,2,2,2,2,2,2,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,2) 

r_RCT = structure(.Data=c(45,NA,NA,NA,NA,60,NA,NA, 
          45,NA,NA,NA,NA,32,NA,NA, 
          65,55,NA,NA,NA,NA,NA,NA, 
          5,1,NA,NA,NA,NA,NA,NA, 
          NA,8,NA,NA,NA,12,NA,NA, 
          7,4,NA,NA,NA,NA,NA,NA, 
          51,NA,NA,NA,NA,NA,NA,32, 
          76,NA,NA,NA,NA,NA,NA,57, 
          21,NA,NA,NA,NA,NA,NA,11, 
          NA,NA,NA,NA,19,NA,NA,40, 
          NA,NA,NA,NA,0,NA,NA,0, 
          33,NA,NA,NA,19,NA,8,NA, 
          24,NA,NA,NA,NA,NA,12,NA, 
          NA,NA,NA,NA,NA,NA,64,39, 
          NA,NA,NA,NA,NA,NA,3,12, 
          NA,NA,NA,NA,30,NA,35,NA, 
          8,NA,NA,NA,NA,NA,8,NA, 
          3,NA,NA,NA,NA,NA,0,NA, 
          NA,NA,NA,2,NA,NA,1,NA, 
          NA,NA,6,1,NA,NA,NA,NA, 
          NA,NA,20,7,NA,NA,NA,NA, 
          21,NA,5,NA,NA,NA,NA,NA, 
          NA,NA,4,NA,10,NA,NA,NA, 
          10,NA,1,NA,NA,NA,NA,NA, 
          14,NA,11,NA,NA,NA,NA,NA, 
          22,NA,4,NA,NA,NA,NA,NA, 
          56,NA,30,NA,17,NA,NA,NA, 
          NA,NA,16,NA,11,NA,NA,NA), .Dim=c(28,8)) 
n_RCT = structure(.Data=c(146,1,1,1,1,152,1,1, 
          100,1,1,1,1,100,1,1, 
          226,224,1,1,1,1,1,1, 
          29,29,1,1,1,1,1,1, 
          1,25,1,1,1,30,1,1, 
          20,20,1,1,1,1,1,1, 
          121,1,1,1,1,1,1,131, 
          232,1,1,1,1,1,1,244, 
          78,1,1,1,1,1,1,78, 
          1,1,1,1,195,1,1,201, 
          1,1,1,1,20,1,1,17, 
          100,1,1,1,100,1,100,1, 
          74,1,1,1,1,1,76,1, 
          1,1,1,1,1,1,259,125, 
          1,1,1,1,1,1,65,64, 
          1,1,1,1,225,1,225,1, 
          61,1,1,1,1,1,136,1, 
          48,1,1,1,1,1,48,1, 
          1,1,1,34,1,1,32,1, 
          1,1,95,94,1,1,1,1, 
          1,1,154,155,1,1,1,1, 
          54,1,54,1,1,1,1,1, 
          1,1,66,1,65,1,1,1, 
          25,1,25,1,1,1,1,1, 
          38,1,72,1,1,1,1,1, 
          72,1,138,1,1,1,1,1, 
          134,1,137,1,131,1,1,1, 
          1,1,109,1,106,1,1,1), .Dim=c(28,8)) 
dataR <- list(nS=28, nT=8, ref=2, t=t_RCT, na=na_RCT, r=r_RCT, n=n_RCT) 
initR<-list(list(u=rep(0,28), tau=0.5),list(u=rep(0.2,28), tau=0.7)) 
Params<-c("u","OR") 


ModelFit<-jags(data=dataR, inits=initR, Params, n.chains=2, 
n.iter=5000, n.burnin=2500, model.file=Model, n.thin=5) 
Result<-ModelFit$BUGSoutput$summary 


write.table(round(Result,digits=3), 
"Results.txt",row.names=T,col.names=T) 
DIC<- ModelFit$BUGSoutput$DIC 
write.table(round(DIC,digits=3), "Dic.txt",row.names=T,col.names=T) 

postscript("PostDen.ps") 
ModelFit.mcmc <- as.mcmc(ModelFit) 
densplot(ModelFit.mcmc) 
dev.off() 

Answer 1

您與對象t，你的[R環境中，是t_RCT子集化您的數據。該對象在其中具有NA值。因此，舉例來說，如果i = 1和k = 3，那麼你正試圖子集對象p在JAGS爲：

p[i,t[i,k]] = p[1,NA]

你不能子集這樣的，因爲行和列必須被索引爲整數。