Final update today [R for BE/BA]

posted by ElMaestro  – Denmark, 2020-07-12 22:27 (461 d 12:28 ago) – Posting: # 21679
Views: 13,198

(edited by ElMaestro on 2020-07-12 23:51)


rm(list=ls(all=TRUE))
 

######
######   Section 1: Household things
######



CreateX=function(D)
{
 ##first the two treatments
 TrtT=as.numeric(as.character(D$Trt)=="T")
 TrtR=as.numeric(as.character(D$Trt)=="R")
 X=cbind(TrtT, TrtR)
 R= qr(X)$rank

 ## subjects: in a mixed model with subj as random
 ## we do not do subjects also as fixed, therefore they are #'ed away here
 ## for (s in unique(D$Subj))
 ## {
 ## v=as.numeric(D$Subj==s)
 ## #print(v)
 ## XX=data.frame(X, v)
 ## names(XX)[ncol(XX)] = paste("S", s, sep="")
 ## rnk=qr(XX)$rank
 ## if (rnk>R)
  ##  {
  ##     X=XX
  ##     R=rnk
  ##  }
  ## }
 ##now the Pers
 for (p in unique(D$Per))
 {
  v=as.numeric(D$Per==p)
  #print(v)
  XX=data.frame(X, v)
  names(XX)[ncol(XX)] = paste("P", p, sep="")
  rnk=qr(XX)$rank
  if (rnk>R)
    {
       X=XX
       R=rnk
    }
 }

 for (q in unique(D$Seq))
 {
  v=as.numeric(D$Seq==q)
  #print(v)
  XX=data.frame(X, v)
  names(XX)[ncol(XX)] = paste("Q", q, sep="")
  rnk=qr(XX)$rank
  if (rnk>R)
    {
       X=XX
       R=rnk
    }
 }
 return(as.matrix(X))
}




Create.CovM=function(Params)
##block diagonal covariance matrix
{
  varT=Params[1]
  varBR=Params[2]
  varWR=Params[3]
  varRT=Params[4]
  #cat("Vars:", varT, varBR, varWR,"\n")

  Nobs=length(D$Y)
  V=matrix(0,ncol=Nobs, nrow=Nobs)
  for (iRow in 1:Nobs)
  for (iCol in 1:Nobs)
  {
   
   ## the diagonal
   if (iCol==iRow)
    {
      if (D$Trt[iRow]=="T") V[iRow,iCol]=V[iRow,iCol]+varT
      if (D$Trt[iRow]=="R") V[iRow,iCol]=V[iRow,iCol]+varWR +varBR
    }

   ## off diagonal
   if (iCol!=iRow)
   if (D$Subj[iRow]==D$Subj[iCol])
    {
     if (D$Trt[iCol]==D$Trt[iRow]) V[iRow,iCol]= V[iRow,iCol]+varBR
     if (D$Trt[iCol]!=D$Trt[iRow]) V[iRow,iCol]= V[iRow,iCol]+varRT
    }
  }
  return(as.matrix(V))
}

######
######   Section 2: Matrix things
######

Obj.F12=function(Pars)
##this is line 3 of page 10 of:
##http://people.csail.mit.edu/xiuming/docs/tutorials/reml.pdf
{
  CovM=Create.CovM(Pars)

  A= -0.5*log(det(CovM))
  B= -0.5*log(det(t(X) %*% solve(CovM) %*% X))
  est.b = solve(t(X) %*% solve(CovM) %*% X) %*% t(X) %*% solve(CovM) %*% y
  tmp= y - X %*% est.b
  C=-0.5 *(t(tmp) %*% solve(CovM) %*% tmp)
  return(A+B+C)
}






####
#### section 3: execution
####

Some.Initial.Guesses=function(foo)
{
 #guess varT
 D1=subset(D, (D$Trt=="T"))
 m=lm(log(Y)~factor(Seq)+factor(Per)   , data=D1)
 varT=anova(m)["Residuals", "Mean Sq"]  #guess VarWR
 D1=subset(D, (D$Trt=="R"))
 m=lm(log(Y)~factor(Seq)+factor(Per)+factor(Subj)  , data=D1)
 varWR=anova(m)["Residuals", "Mean Sq"]  #guess varBR
 S=unique(D$Subj)
 v=NULL
 for (s in S)
 {
  Dx=subset(D, (D$Subj==s) & (D$Trt=="R"))
  v=c(v, mean(log(Dx$Y)))
 }
 varBR=var(v)-varWR
 varRT=0.5*(varT+varBR)

 rslt=c(varT, varBR, varWR, varRT)
 return(rslt)
}




D=read.csv("EMAII.a.csv" , header=T, sep="\t") ##public = easier
X=CreateX(D) ##public = easier
y=log(D$Y) ##public = easier


MyREML=function(foo.bar)
 
{
  L=Some.Initial.Guesses(0)
  print(L)
  parIni=L
  F=optim(par=parIni, fn=Obj.F12,
      control=list(reltol=1e-9, trace=T, fnscale=-1))
  Nms=c("varT","varBR", "varWR", "varRT")
  X=data.frame(Nms, F$par, parIni)
  names(X)=c("Var.Component", "Value", "Ini.value")
  return(X)
}
 
MyREML(0)



which gives
  Var.Component      Value  Ini.value
1          varT 0.07050210 0.06841615
2         varBR 0.03621403 0.02776728
3         varWR 0.01324510 0.01240137
4         varRT 0.04563784 0.04809171


By the way: You can adjust how many decimals you want on e.g. varWR (~s2WR) through the reltol setting. Use e.g. 1e-12 to get 0.0.01324652 with just a few more iterations.



Job done?

Pass or fail!
ElMaestro

Complete thread:

Activity
 Admin contact
21,730 posts in 4,544 threads, 1,543 registered users;
online 3 (0 registered, 3 guests [including 3 identified bots]).
Forum time: Sunday 10:56 CEST (Europe/Vienna)

Be very, very careful what you put into that head,
because you will never, ever get it out.    Thomas Wolsey

The Bioequivalence and Bioavailability Forum is hosted by
BEBAC Ing. Helmut Schütz
HTML5