R/med2mcp.R

In musto101/wilcox_R: What the package does (short line)

med2mcp <-
function(J,K,x,grp=c(1:p),p=J*K,tr=.2,nboot=NA,alpha=.05,SEED=TRUE,pr=TRUE,
bhop=FALSE){
#
#  Perform multiple comparisons for  J by K anova using medians with
#   using a bpercentile bootstrap method
#
#
#  The R variable data is assumed to contain the raw
#  data stored in a matrix or in list mode.
#  If stored in list mode, data[[1]] contains the data
#  for the first level of both factors: level 1,1.
#  data[[2]] is assumed to contain the data for level 1 of the
#  first factor and level 2 of the second: level 1,2
#  data[[K]] is the data for level 1,K
#  data[[K+1]] is the data for level 2,1, data[2K] is level 2,K, etc.
#
#  It is assumed that data has length JK, the total number of
#  groups being tested, but a subset of the data can be analyzed
#  using grp
#
if(SEED)set.seed(2)
if(is.list(x))x<-elimna(matl(x))
if(is.matrix(x))x<-elimna(x)
data<-x
if(is.matrix(data))data<-listm(data)
if(!is.list(data))stop("Data are not stored in list mode or a matrix")
if(p!=length(data)){
print("The total number of groups, based on the specified levels, is")
print(p)
print("The number of groups stored in x is")
print(length(data))
print("Warning: These two values are not equal")
}
if(p!=length(grp))stop("Apparently a subset of the groups was specified that does not match the total number of groups indicated by the values for J and K.")
temp=con2way(J,K)
conA<-temp$conA
conB<-temp$conB
conAB<-temp$conAB
if(pr)print("Taking bootstrap samples")
Factor.A<-medpb(x,con=conA,alpha=alpha,nboot=nboot,bhop=bhop,SEED=FALSE)
Factor.B<-medpb(x,con=conB,alpha=alpha,nboot=nboot,bhop=bhop,SEED=FALSE)
Factor.AB<-medpb(x,con=conAB,alpha=alpha,nboot=nboot,bhop=bhop,SEED=FALSE)
list(Factor.A=Factor.A,Factor.B=Factor.B,Factor.AB=Factor.AB,bhop=bhop,SEED=FALSE)
}