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821.2777778	795.9666667	776.8666667	807.8666667
1379.188889	1427.1	1342.2	1439.466667
982.5666667	996.4666667	994	1090.633333
1664.533333	1783.333333	1923.733333	1867.7
716.8333333	706	752.6666667	783
996.8555556	925.0333333	925.1	906.3666667
915.6777778	1078.2	1074.833333	935.5
1223.977778	1193.533333	1161.066667	1251.3
868.3111111	876.4666667	833.4666667	853.6666667
1023.244444	1092.133333	1015.866667	1092.566667
1005.933333	973.9333333	945.3666667	1001.533333
1334.533333	1426.066667	1702.5	1414.566667
1292.633333	1305.233333	1256.933333	1215.633333
1076.655556	1090.133333	1127.333333	1064.7
953.6222222	895.9666667	935.9333333	957.3666667
909.9	954.8	927.3333333	1052.3
1161.388889	1118.7	1181.366667	1218.5
1526.455556	1431.266667	1774	1405.233333
867.5666667	818	823.3	894.6
1070.422222	1059.866667	1071.833333	1120.233333
951.6555556	1002.066667	880.3666667	957.5333333
737.4	701.0333333	705.1666667	711.1333333
1943.633333	2076.466667	1996.433333	1903.7
816.4555556	810.7	789	861.1333333
787.5	741.7666667	751.8	743.4333333

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')