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588.8444444 591.4 559.3 593.3333333
992.1333333 1049.3 923.0666667 1049.866667
732.7222222 764.8 665.4333333 714.3666667
1615.9 1692.4 1667.333333 1750.766667
481.4444444 499.8333333 470.8333333	481.3
660.6444444 625.0666667 650.7 635.8666667
839.6111111 961.4 924.1666667 928.9666667
583.6222222 583.5333333 596.2 601.9
456.0777778 458.3666667 477.9666667 503.1333333
648.6222222 685 738.7333333 828.7666667
727.5666667 741.2 676.2666667 641.3
1197.9 873.7333333 1240.566667 1486.266667
1060.311111 1089.133333 1180.533333 1267.466667
888.2666667 929.7 903.9 993.9666667
481.7444444 470.2666667 486.2666667 467.6666667
788.5888889 803.3333333 825.4 791.4333333
548.0666667 565.3666667 514 580.1
940.2444444 1126.9 937.0666667 1067.1
584.5111111 582.3333333 625.8 581.3333333
519.3444444 549 499.4666667 519.4666667
485.8444444 511.5666667 470.0666667 498.9
943.0555556 802.5666667 788.6 1279.666667
479.9555556 494.1 471.0333333 444.6333333
390.2111111 411.5 402.0666667 363.4666667

rm2mcp<-function(J,K,x,est=tmean,alpha=.05,grp=NA,dif=T,nboot=NA,
plotit=FALSE,BA=F,hoch=F,...){
JK <- J * K
if(is.matrix(x))
x <- listm(x)
if(!is.na(grp[1])) {
yy <- x
for(j in 1:length(grp))
x[[j]] <- yy[[grp[j]]]
}
if(!is.list(x))
stop('Data must be stored in list mode or a matrix.')
for(j in 1:JK) {
xx <- x[[j]]
x[[j]] <- xx[!is.na(xx)]
}
temp<-con2way(J,K)
conA<-temp$conA
conB<-temp$conB
conAB<-temp$conAB
ncon <- max(nrow(conA), nrow(conB), nrow(conAB))
FacA<-rmmcppb(x,con=conA,est=est,plotit=plotit,dif=dif,grp=grp,
nboot=nboot,BA=T,hoch=F,...)
FacB<-rmmcppb(x,con=conB,est=est,plotit=plotit,dif=dif,grp=grp,
nboot=nboot,BA=T,hoch=F,...)
FacAB<-rmmcppb(x,con=conAB,est=est,plotit=plotit,dif=dif,grp=grp,
nboot=nboot,BA=T,hoch=F,...)
list(Factor.A=FacA,Factor.B=FacB,Factor.AB=FacAB)
}
listm<-function(x){
if(is.null(dim(x)))stop('The argument x must be a matrix or data frame')
y<-list()
for(j in 1:ncol(x))y[[j]]<-x[,j]
y
}
con2way<-function(J,K){
JK <- J * K
Ja<-(J^2-J)/2
Ka<-(K^2-K)/2
JK<-J*K
conA<-matrix(0,nrow=JK,ncol=Ja)
ic<-0
for(j in 1:J){
for(jj in 1:J){
if(j < jj){
ic<-ic+1
mat<-matrix(0,nrow=J,ncol=K)
mat[j,]<-1
mat[jj,]<-0-1
conA[,ic]<-t(mat)
}}}
conB<-matrix(0,nrow=JK,ncol=Ka)
ic<-0
for(k in 1:K){
for(kk in 1:K){
if(kic<-ic+1
mat<-matrix(0,nrow=J,ncol=K)
mat[,k]<-1
mat[,kk]<-0-1
conB[,ic]<-t(mat)
}}}
conAB<-matrix(0,nrow=JK,ncol=Ka*Ja)
ic<-0
for(j in 1:J){
for(jj in 1:J){
if(j < jj){
for(k in 1:K){
for(kk in 1:K){
if(kic<-ic+1
mat<-matrix(0,nrow=J,ncol=K)
mat[j,k]<-1
mat[j,kk]<-0-1
mat[jj,k]<-0-1
mat[jj,kk]<-1
}
conAB[,ic]<-t(mat)
}}}}}
list(conA=conA,conB=conB,conAB=conAB)
}
rmmcppbd<-function(x,y=NULL,alpha=.05,con=0,est=onestep,plotit=TRUE,grp=NA,nboot=NA,
hoch=T,SEED=TRUE,...){
if(!is.null(y[1]))x<-cbind(x,y)
if(!is.list(x) && !is.matrix(x))stop('Data must be stored in a matrix or in list mode.')
if(is.list(x)){
if(is.matrix(con)){
if(length(x)!=nrow(con))stop('The number of rows in con is not equal to the number of groups.')
}}
if(is.list(x)){
mat<-matl(x)
}
if(is.matrix(x) && is.matrix(con)){
if(ncol(x)!=nrow(con))stop('The number of rows in con is not equal to the number of groups.')
mat<-x
}
if(is.matrix(x))mat<-x
if(!is.na(sum(grp)))mat<-mat[,grp]
x<-mat
mat<-elimna(mat) # Remove rows with missing values.
x<-mat
J<-ncol(mat)
n=nrow(mat)
if(n>=80)hoch=T
Jm<-J-1
if(sum(con^2)==0){
d<-(J^2-J)/2
con<-matrix(0,J,d)
id<-0
for (j in 1:Jm){
jp<-j+1
for (k in jp:J){
id<-id+1
con[j,id]<-1
con[k,id]<-0-1
}}}
d<-ncol(con)
if(is.na(nboot)){
nboot<-5000
if(d<=10)nboot<-3000
if(d<=6)nboot<-2000
if(d<=4)nboot<-1000
}
n<-nrow(mat)
crit.vec<-alpha/c(1:d)
connum<-ncol(con)
xx<-x%*%con
xx<-as.matrix(xx)
if(SEED)set.seed(2) # set seed of random number generator so that
psihat<-matrix(0,connum,nboot)
bvec<-matrix(NA,ncol=connum,nrow=nboot)
data<-matrix(sample(n,size=n*nboot,replace=T),nrow=nboot)
if(ncol(xx)==1){
for(ib in 1:nboot)psihat[1,ib]<-est(xx[data[ib,]],...)
}
if(ncol(xx)>1){
for(ib in 1:nboot)psihat[,ib]<-apply(xx[data[ib,],],2,est,...)
}
test<-1
for (ic in 1:connum){
test[ic]<-(sum(psihat[ic,]>0)+.5*sum(psihat[ic,]==0))/nboot
test[ic]<-min(test[ic],1-test[ic])
}
test<-2*test
ncon<-ncol(con)
if(alpha==.05){
dvec<-c(.025,.025,.0169,.0127,.0102,.00851,.0073,.00639,.00568,.00511)
if(ncon > 10){
avec<-.05/c(11:ncon)
dvec<-c(dvec,avec)
}}
if(alpha==.01){
dvec<-c(.005,.005,.00334,.00251,.00201,.00167,.00143,.00126,.00112,.00101)
if(ncon > 10){
avec<-.01/c(11:ncon)
dvec<-c(dvec,avec)
}}
if(alpha != .05 && alpha != .01){
dvec<-alpha/c(1:ncon)
dvec[2]<-alpha/2
}
if(hoch)dvec<-alpha/(2*c(1:ncon))
dvec<-2*dvec
if(plotit && connum==1){
plot(c(psihat[1,],0),xlab='',ylab='Est. Difference')
points(psihat[1,])
abline(0,0)
}
temp2<-order(0-test)
ncon<-ncol(con)
zvec<-dvec[1:ncon]
sigvec<-(test[temp2]>=zvec)
output<-matrix(0,connum,6)
dimnames(output)<-list(NULL,c('con.num','psihat','p.value','p.crit','ci.lower','ci.upper'))
tmeans<-apply(xx,2,est,...)
psi<-1
icl<-round(dvec[ncon]*nboot/2)+1
icu<-nboot-icl-1
for (ic in 1:ncol(con)){
output[ic,2]<-tmeans[ic]
output[ic,1]<-ic
output[ic,3]<-test[ic]
output[temp2,4]<-zvec
temp<-sort(psihat[ic,])
output[ic,5]<-temp[icl]
output[ic,6]<-temp[icu]
}
num.sig<-sum(output[,3]<=output[,4])
list(output=output,con=con,num.sig=num.sig)
}
rmmcppb<-function(x,y=NULL,alpha=.05,con=0,est=onestep,plotit=TRUE,dif=T,grp=NA,nboot=NA,BA=F,hoch=F,xlab='Group 1',ylab='Group 2',pr=TRUE,SEED=TRUE,...){
if(dif){
if(pr)print('dif=T, so analysis is done on difference scores')
temp<-rmmcppbd(x,y=y,alpha=.05,con=con,est,plotit=plotit,grp=grp,nboot=nboot,
hoch=T,...)
output<-temp$output
con<-temp$con
}
if(!dif){
if(pr){
print('dif=F, so analysis is done on marginal distributions')
if(!BA)print('With M-estimator or MOM, suggest using BA=T and hoch=T')
}
if(!is.null(y[1]))x<-cbind(x,y)
if(!is.list(x) && !is.matrix(x))stop('Data must be stored in a matrix or in list mode.')
if(is.list(x)){
if(is.matrix(con)){
if(length(x)!=nrow(con))stop('The number of rows in con is not equal to the number of groups.')
}}
if(is.list(x)){
mat<-matl(x)
}
if(is.matrix(x) && is.matrix(con)){
if(ncol(x)!=nrow(con))stop('The number of rows in con is not equal to the number of groups.')
mat<-x
}
if(is.matrix(x))mat<-x
if(!is.na(sum(grp)))mat<-mat[,grp]
mat<-elimna(mat) # Remove rows with missing values.
x<-mat
J<-ncol(mat)
xcen<-x
for(j in 1:J)xcen[,j]<-x[,j]-est(x[,j])
Jm<-J-1
if(sum(con^2)==0){
d<-(J^2-J)/2
con<-matrix(0,J,d)
id<-0
for (j in 1:Jm){
jp<-j+1
for (k in jp:J){
id<-id+1
con[j,id]<-1
con[k,id]<-0-1
}}}
d<-ncol(con)
if(is.na(nboot)){
if(d<=4)nboot<-1000
if(d>4)nboot<-5000
}
n<-nrow(mat)
crit.vec<-alpha/c(1:d)
connum<-ncol(con)
if(SEED)set.seed(2) # set seed of random number generator so that
xbars<-apply(mat,2,est)
psidat<-NA
for (ic in 1:connum)psidat[ic]<-sum(con[,ic]*xbars)
psihat<-matrix(0,connum,nboot)
psihatcen<-matrix(0,connum,nboot)
bvec<-matrix(NA,ncol=J,nrow=nboot)
bveccen<-matrix(NA,ncol=J,nrow=nboot)
if(pr)print('Taking bootstrap samples. Please wait.')
data<-matrix(sample(n,size=n*nboot,replace=T),nrow=nboot)
for(ib in 1:nboot){
bvec[ib,]<-apply(x[data[ib,],],2,est,...)
bveccen[ib,]<-apply(xcen[data[ib,],],2,est,...)
}
test<-1
bias<-NA
for (ic in 1:connum){
psihat[ic,]<-apply(bvec,1,bptdpsi,con[,ic])
psihatcen[ic,]<-apply(bveccen,1,bptdpsi,con[,ic])
bias[ic]<-sum((psihatcen[ic,]>0))/nboot-.5
ptemp<-(sum(psihat[ic,]>0)+.5*sum(psihat[ic,]==0))/nboot
if(BA)test[ic]<-ptemp-.1*bias[ic]
if(!BA)test[ic]<-ptemp
test[ic]<-min(test[ic],1-test[ic])
test[ic]<-max(test[ic],0)
}
test<-2*test
ncon<-ncol(con)
if(alpha==.05){
dvec<-c(.025,.025,.0169,.0127,.0102,.00851,.0073,.00639,.00568,.00511)
dvecba<-c(.05,.025,.0169,.0127,.0102,.00851,.0073,.00639,.00568,.00511)
if(ncon > 10){
avec<-.05/c(11:ncon)
dvec<-c(dvec,avec)
}}
if(alpha==.01){
dvec<-c(.005,.005,.00334,.00251,.00201,.00167,.00143,.00126,.00112,.00101)
dvecba<-c(.01,.005,.00334,.00251,.00201,.00167,.00143,.00126,.00112,.00101)
if(ncon > 10){
avec<-.01/c(11:ncon)
dvec<-c(dvec,avec)
}}
if(alpha != .05 && alpha != .01){
dvec<-alpha/c(1:ncon)
dvecba<-dvec
dvec[2]<-alpha
}
if(hoch)dvec<-alpha/c(1:ncon)
dvec<-2*dvec
dvecba<-dvec
if(plotit && ncol(bvec)==2){
z<-c(0,0)
one<-c(1,1)
plot(rbind(bvec,z,one),xlab=xlab,ylab=ylab,type='n')
points(bvec)
totv<-apply(x,2,est,...)
cmat<-var(bvec)
dis<-mahalanobis(bvec,totv,cmat)
temp.dis<-order(dis)
ic<-round((1-alpha)*nboot)
xx<-bvec[temp.dis[1:ic],]
xord<-order(xx[,1])
xx<-xx[xord,]
temp<-chull(xx)
lines(xx[temp,])
lines(xx[c(temp[1],temp[length(temp)]),])
abline(0,1)
}
temp2<-order(0-test)
ncon<-ncol(con)
zvec<-dvec[1:ncon]
if(BA)zvec<-dvecba[1:ncon]
sigvec<-(test[temp2]>=zvec)
output<-matrix(0,connum,6)
dimnames(output)<-list(NULL,c('con.num','psihat','p.value','p.sig','ci.lower','ci.upper'))
tmeans<-apply(mat,2,est,...)
psi<-1
output[temp2,4]<-zvec
for (ic in 1:ncol(con)){
output[ic,2]<-sum(con[,ic]*tmeans)
output[ic,1]<-ic
output[ic,3]<-test[ic]
temp<-sort(psihat[ic,])
icl<-round(output[ic,4]*nboot/2)+1
icu<-nboot-(icl-1)
output[ic,5]<-temp[icl]
output[ic,6]<-temp[icu]
}
}
num.sig<-sum(output[,3]<=output[,4])
list(output=output,con=con,num.sig=num.sig)
}
matl<-function(x){
J=length(x)
nval=NA
for(j in 1:J)nval[j]=length(x[[j]])
temp<-matrix(NA,ncol=J,nrow=max(nval))
for(j in 1:J)temp[1:nval[j],j]<-x[[j]]
temp
}
Aband<-function(x,alpha=.05,plotit=TRUE,sm=T,SEED=TRUE,nboot=500,grp=c(1:4),
xlab='X (First Factor)',ylab='Delta',crit=NA,print.all=F,plot.op=F){
if(!is.list(x) && !is.matrix(x))stop('store data in list mode or a matrix')
if(SEED)set.seed(2)
if(is.matrix(x))x<-listm(x)
for(j in 1:length(x))x[[j]]=elimna(x[[j]])/2
if(length(grp)<4)stop('There must be at least 4 groups')
if(length(x)!=4)stop('The argument grp must have 4 values')
x<-x[grp]
n<-c(length(x[[1]]),length(x[[2]]),length(x[[3]]),length(x[[4]]))
vals<-NA
y<-list()
if(is.na(crit)){
print('Approximating critical value. Please wait.')
for(i in 1:nboot){
for(j in 1:4)
y[[j]]<-rnorm(n[j])
temp<-ks.test(outer(y[[1]],y[[2]],FUN='+'),outer(y[[3]],y[[4]],FUN='+'))
vals[i]<-temp[1]$statistic
}
vals<-sort(vals)
ic<-(1-alpha)*nboot
crit<-vals[ic]
}
if(plot.op){
plotit<-F
g2plot(v1,v2)
}
output<-sband(outer(x[[1]],x[[2]],FUN='+'),outer(x[[3]],x[[4]],FUN='+'),
plotit=plotit,crit=crit,flag=F,sm=sm,xlab=xlab,ylab=ylab)
if(!print.all){
numsig<-output$numsig
ks.test.stat<-ks.test(outer(x[[1]],x[[2]],FUN='+'),
outer(x[[3]],x[[4]],FUN='+'))$statistic
output<-matrix(c(numsig,crit,ks.test.stat),ncol=1)
dimnames(output)<-list(c('number sig','critical value','KS test statistics'),
NULL)
}
output
}
elimna<-function(m){
if(is.null(dim(m)))m<-as.matrix(m)
ikeep<-c(1:nrow(m))
for(i in 1:nrow(m))if(sum(is.na(m[i,])>=1))ikeep[i]<-0
elimna<-m[ikeep[ikeep>=1],]
elimna
}
tmean<-function(x,tr=.2,na.rm=FALSE){
if(na.rm)x<-x[!is.na(x)]
val<-mean(x,tr)
val
}
bptdpsi<-function(x,con){
bptdpsi<-sum(con*x)
bptdpsi
}
bptdsub<-function(isub,x,tr,con){
h1 <- nrow(x) - 2 * floor(tr * nrow(x))
se<-0
for(j in 1:ncol(x)){
for(k in 1:ncol(x)){
djk<-(nrow(x) - 1) * wincor(x[isub,j],x[isub,k], tr)$cov
se<-se+con[j]*con[k]*djk
}
}
se/(h1*(h1-1))
}
y<-t(y)
head(y)
dimnames(y)
bitmap(file='test1.png')
boxplot(y)
dev.off()
bitmap(file='test2.png')
layout(matrix(c(1,2,3,4), 2, 2))
(rmout<-rm2mcp(2,2,y, plotit=TRUE) )
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Information on data table  format.',3,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'For this repeated measures design you must')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'have only one participant /subject on each row.')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'The order of factors is also constrained so that')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'for factors A B each with two levels the column order is.')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'A1B1 A1B2 A2B1 A2B2 as given in the default example.')
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='myinfo1.tab')
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,names(rmout)[1],3,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,dimnames(rmout$Factor.A$output)[[2]][1],header=TRUE)
a<-table.element(a,rmout$Factor.A$output[1])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,dimnames(rmout$Factor.A$output)[[2]][2],header=TRUE)
a<-table.element(a,rmout$Factor.A$output[2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,dimnames(rmout$Factor.A$output)[[2]][3],header=TRUE)
a<-table.element(a,rmout$Factor.A$output[3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,dimnames(rmout$Factor.A$output)[[2]][4],header=TRUE)
a<-table.element(a,rmout$Factor.A$output[4])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,dimnames(rmout$Factor.A$output)[[2]][5],header=TRUE)
a<-table.element(a,rmout$Factor.A$output[5])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,dimnames(rmout$Factor.A$output)[[2]][6],header=TRUE)
a<-table.element(a,rmout$Factor.A$output[6])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,names(rmout)[2],3,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,dimnames(rmout$Factor.B$output)[[2]][1],header=TRUE)
a<-table.element(a,rmout$Factor.B$output[1])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,dimnames(rmout$Factor.B$output)[[2]][2],header=TRUE)
a<-table.element(a,rmout$Factor.B$output[2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,dimnames(rmout$Factor.B$output)[[2]][3],header=TRUE)
a<-table.element(a,rmout$Factor.B$output[3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,dimnames(rmout$Factor.B$output)[[2]][4],header=TRUE)
a<-table.element(a,rmout$Factor.B$output[4])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,dimnames(rmout$Factor.B$output)[[2]][5],header=TRUE)
a<-table.element(a,rmout$Factor.B$output[5])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,dimnames(rmout$Factor.B$output)[[2]][6],header=TRUE)
a<-table.element(a,rmout$Factor.B$output[6])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable2.tab')
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,names(rmout)[3],3,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,dimnames(rmout$Factor.AB$output)[[2]][1],header=TRUE)
a<-table.element(a,rmout$Factor.AB$output[1])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,dimnames(rmout$Factor.AB$output)[[2]][2],header=TRUE)
a<-table.element(a,rmout$Factor.AB$output[2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,dimnames(rmout$Factor.AB$output)[[2]][3],header=TRUE)
a<-table.element(a,rmout$Factor.AB$output[3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,dimnames(rmout$Factor.AB$output)[[2]][4],header=TRUE)
a<-table.element(a,rmout$Factor.AB$output[4])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,dimnames(rmout$Factor.AB$output)[[2]][5],header=TRUE)
a<-table.element(a,rmout$Factor.AB$output[5])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,dimnames(rmout$Factor.AB$output)[[2]][6],header=TRUE)
a<-table.element(a,rmout$Factor.AB$output[6])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')