rmutil: Utilities for Nonlinear Regression and Repeated Measurements Models

Documented in as.data.frame as.data.frame.repeated as.data.frame.response as.data.frame.tccov as.data.frame.tvcov as.matrix as.matrix.repeated as.matrix.response as.matrix.tccov as.matrix.tvcov covariates covariates.repeated covariates.tccov covariates.tvcov covind covind.default delta delta.repeated delta.response description description.default description.repeated dftorep formula.repeated formula.tccov lvna names.repeated names.response names.tccov names.tvcov nesting nesting.repeated nesting.response nobs nobs.data.frame nobs.default nobs.response nobs.tvcov plot.repeated plot.response print.repeated print.response print.tccov print.tvcov response response.repeated response.response resptype resptype.repeated resptype.response restovec rmna tcctomat times times.default times.response transform.repeated transform.response transform.tccov transform.tvcov tvctomat units units.default units.repeated weights.repeated weights.response

#
#  rmutil : A Library of Special Functions for Repeated Measurements
#  Copyright (C) 1998, 1999, 2000, 2001 J.K. Lindsey
#
#  This program is free software; you can redistribute it and/or modify
#  it under the terms of the GNU General Public Licence as published by
#  the Free Software Foundation; either version 2 of the Licence, or
#  (at your option) any later version.
#
#  This program is distributed in the hope that it will be useful,
#  but WITHOUT ANY WARRANTY; without even the implied warranty of
#  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
#  GNU General Public Licence for more details.
#
#  You should have received a copy of the GNU General Public Licence
#  along with this program; if not, write to the Free Software
#  Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA.
#
#  SYNOPSIS
#
#     restovec(response, times=NULL, nest=NULL, coordinates=NULL,
#	censor=NULL, totals=NULL, weights=NULL, delta=NULL, type=NULL,
#	names=NULL, units=NULL, oldresponse=NULL, description=NULL)
#     tcctomat(ccov, names=NULL, units=NULL, oldtccov=NULL, dataframe=TRUE,
#     description=NULL)
#     tvctomat(tvcov, names=NULL, units=NULL, interaction=NULL, ccov=NULL,
#	oldtvcov=NULL, dataframe=TRUE, description=NULL)
#     rmna(response, tvcov=NULL, ccov=NULL)
#     lvna(response, tvcov=NULL, ccov=NULL)
#     dftorep(dataframe, response, id=NULL, times=NULL, censor=NULL,
#	totals=NULL, weights=NULL, nest=NULL, delta=NULL,
#	coordinates=NULL, type=NULL, ccov=NULL, tvcov=NULL, na.rm=TRUE)
#     as.data.frame(z)
#     as.matrix(z)
#     covariates(z, nind=NULL, names=NULL)
#     covind(z)
#     delta(z, nind=NULL, names=NULL)
#     formula(z)
#     names(z)
#     nesting(z, nind=NULL)
#     nobs(z)
#     plot.response(z, nind=NULL, name=NULL, nest=1, ccov=NULL, add=FALSE,
#	lty=NULL, pch=NULL, main=NULL, ylim=NULL, xlim=NULL, xlab=NULL,
#	ylab=NULL, ...)
#     plot.repeated(z, name=NULL, nind=NULL, ccov=NULL, add=FALSE, lty=NULL,
#	main=NULL, ylim=NULL, xlim=NULL, xlab=NULL, ylab=NULL, ...)
#     print(z)
#     response(z, nind=NULL, names=NULL)
#     times(z, nind=NULL)
#     transform(z, ...)
#     weights(z, nind=NULL)
#
#  DESCRIPTION
#
#    Utility functions for converting repeated measurements data to R objects

### function to create a response object
###
restovec <- function(response=NULL, times=NULL, nest=NULL, coordinates=NULL,
	censor=NULL, totals=NULL, weights=NULL, delta=NULL, type=NULL,
	names=NULL, units=NULL, oldresponse=NULL, description=NULL){
if(is.null(response))stop("A response must be supplied")
#
# check type
#
mvr <- length(names)>1
if(!is.null(type)){
	tmp <- NULL
	for(i in 1:length(type))
		tmp <- c(tmp,match.arg(type[i],
			c("nominal","ordinal","discrete","duration","continuous","unknown")))
	type <- tmp
	if(!mvr)mvr <- length(type)>1}
#
# initial values
#
nind <- 0
tnest <- nobs <- y <- NULL
#
# check if times are required
#
ttime <- !is.logical(times)||times
if((ttime&&is.logical(times))||!ttime)times <- NULL
#
# handle various forms of response
#
if(is.null(names))names <- paste(deparse(substitute(response)))
if(is.vector(response,mode="numeric")){
#
# numerical vector supplied: either univariate independent
#   observations or one time series
#
	y <- response
	# check if independent observations or one time series
	nobs <- if(is.null(times)) 1 else length(response)
	# check times
	if(is.vector(times,mode="numeric")){
		if(length(times)!=length(y))
			stop("times must be the same length as the response")}
	else if(!is.null(times))stop("times must be a vector")
	# check censor indicator
	if(is.vector(censor,mode="numeric")){
		if(length(censor)!=length(y)){
			if(length(censor)==1)
				censor <- c(rep(1,length(y)-1),censor)
			else stop("censor must be the same length as the response")}}
	else if(!is.null(censor))stop("censor must be a scalar or vector")
	# check coordinates
	if(!is.null(coordinates)&&(!is.matrix(coordinates)||(is.matrix(coordinates)&&length(dim(coordinates))!=2&&dim(coordinates)[2]!=2&&dim(coordinates)[1]!=length(y))))
		stop("coordinates must be a matrix with two columns and the same number of rows as the length of response")
	# check totals
	if(is.vector(totals,mode="numeric")){
		if(length(totals)!=length(y)){
			if(length(totals)==1)totals <- rep(totals,length(y))
			else stop("totals must be the same length as the response")}}
	else if(!is.null(totals)) stop("totals must be a vector")
	# check weights
	if(is.vector(weights,mode="numeric")){
		if(length(weights)!=length(y))
		stop("weights must be the same length as the response")}
	else if(!is.null(weights))stop("weights must be a vector")
	# check delta
	if(is.vector(delta,mode="numeric")){
		if(length(delta)!=length(y)){
			if(length(delta)==1)delta <- rep(delta,length(y))
			else stop("delta must be the same length as the response")}}
	else if(!is.null(delta))stop("delta must be a scalar or vector")}
else if(is.array(response)&&length(dim(response))==3){
#
# one multivariate 3-dim array of balanced repeated measurements supplied
#
	nobs <- rep(dim(response)[2],dim(response)[1])
	if(length(names)==1)names <- paste(names,1:dim(response)[3],sep="")
	# check times
	if(is.null(times)){
		if(is.null(censor)&&ttime)
			times <- as.double(rep(1:dim(response)[2],dim(response)[1]))}
	else if(is.matrix(times)){
		if(dim(times)[2]!=dim(response)[2]||dim(times)[1]!=dim(response)[1])
			stop("times matrix must be the same size as first two dimensions of array of responses")
		# time steps can be 0 but not negative
		for(i in 1:dim(response)[1])
			if(any(diff(times[i,])<0,na.rm=TRUE))
			stop(paste("negative time step for individual ",i))
		times <- as.vector(t(times))}
	else if(is.vector(times,mode="numeric")) {
		if(is.null(nest)&&any(diff(times)<0,na.rm=TRUE))
			stop("times must be increasing")
		if(length(times)!=dim(response)[2])
			stop("number of times must equal number of response columns")
		times <- rep(times,dim(response)[1])}
	else stop("times must be a vector or matrix")
	# check weights
	if(is.matrix(weights)){
		if(dim(weights)[1]!=dim(response)[1]||dim(weights)[2]!=dim(response)[2])
			stop("weights matrix must be the same size as first two dimensions of array of responses")
		else weights <- as.vector(t(weights))}
	else if(is.vector(weights,mode="numeric")){
		if(length(weights)!=dim(response)[1])
			stop("weights vector must have same length as number of individuals")
		else weights <- rep(weights,rep(dim(response)[2],dim(response)[1]))}
	else if(!is.null(weights))stop("weights must be a vector or matrix")
	# check nesting
	if(is.matrix(nest)){
		if(dim(weights)[1]!=dim(response)[1]||dim(weights)[2]!=dim(response)[2])
			stop("nest matrix must be the same size as first two dimensions of array of responses")
		for(i in 1:dim(nest)[1])
			if(any(diff(nest[i,])!=0&diff(nest[i,])!=1,na.rm=TRUE))
				stop("nest categories must be consecutive increasing integers")
		tnest <- as.vector(t(nest))}
	else if(is.vector(nest,mode="numeric")){
		if(length(nest)!=dim(response)[2])
			stop("nest vector must have same length as number of individuals")
		if(any(diff(nest)!=0&diff(nest)!=1,na.rm=TRUE))
			stop("nest categories must be consecutive increasing integers")
		tnest <- rep(nest,dim(response)[1])}
	else if(!is.null(nest))stop("nest must be a vector or matrix")
	# check censor indicator
	if(is.array(censor)&&length(dim(censor))==3){
		if(any(dim(censor)!=dim(response)))
			stop("censor array must be the same size as array of responses")
		tmp <- NULL
		for(i in 1:dim(response)[3])
			tmp <- cbind(tmp,as.vector(t(censor[,,i])))
		censor <- tmp
		rm(tmp)}
	else if(is.matrix(censor)){
	# if a matrix, corresponds to last observation of each subject
		if(dim(censor)[1]!=dim(response)[1]||dim(censor)[2]!=dim(response)[3])
			stop("censor matrix must have dimensions, number of individuals by number of variables")
		tmp <- array(1,dim(response))
		for(i in 1:dim(response)[3])
			tmp[,dim(tmp)[2],i] <- censor[,i]
		censor <- NULL
		for(i in 1:dim(response)[3])
			censor <- cbind(censor,as.vector(t(tmp[,,i])))
		rm(tmp)}
	else if(!is.null(censor))stop("censor must be a matrix or array")
	# check totals
	if(is.array(totals)&&length(dim(totals))==3){
		if(any(dim(totals)!=dim(response)))
			stop("totals array must be the same size as array of responses")
		tmp <- NULL
		for(i in 1:dim(response)[3])
			tmp <- cbind(tmp,as.vector(t(totals[,,i])))
		totals <- tmp
		rm(tmp)}
	else if(is.matrix(totals)){
		if(dim(totals)[1]!=dim(response)[1]||dim(totals)[2]!=dim(response)[3])
			stop("totals matrix must have dimensions, number of individuals by number of variables")
		for(i in 1:dim(response)[3])
		tmp <- NULL
		for(i in 1:dim(response)[3])
			tmp <- cbind(tmp,rep(totals[,i],rep(dim(response)[2],dim(response)[1])))
		totals <- tmp
		rm(tmp)}
	else if(!is.null(totals))stop("totals must be a matrix or array")
	# check delta
	if(is.array(delta)&&length(dim(delta))==3){
		if(any(dim(delta)!=dim(response)))
			stop("delta array must be the same size as array of responses")
		tmp <- NULL
		for(i in 1:dim(response)[3])
			tmp <- cbind(tmp,as.vector(t(delta[,,i])))
		delta <- tmp
		rm(tmp)}
	else if(is.matrix(delta)){
		if(dim(delta)[1]!=dim(response)[1]||dim(delta)[2]!=dim(response)[3])
			stop("delta matrix must have dimensions, number of individuals by number of variables")
		for(i in 1:dim(response)[3])
		tmp <- NULL
		for(i in 1:dim(response)[3])
			tmp <- cbind(tmp,rep(delta[,i],rep(dim(response)[2],dim(response)[1])))
		delta <- tmp
		rm(tmp)}
	else if(!is.null(delta))stop("delta must be a matrix or array")
	y <- NULL
	for(i in 1:dim(response)[3])y <- cbind(y,as.vector(t(response[,,i])))
	mvr <- TRUE}
else if(mvr&&(is.matrix(response)||is.data.frame(response))){
#
# multivariate matrix or dataframe of independent observations or time
#   series supplied
#
	y <- as.matrix(response)
	# check if independent observations or one time series
	nobs <- if(is.null(times)) 1 else dim(response)[1]
	# check times
	if(is.vector(times,mode="numeric")){
		if(length(times)!=dim(y)[1])
			stop("times must be the same length as the number of responses/variable")}
	else if(!is.null(times))stop("times must be a vector")
	# check weights
	if(is.vector(weights,mode="numeric")){
		if(length(weights)!=dim(y)[1])
		stop("weights must be the same length as the number of responses/variable")}
	else if(!is.null(weights))stop("weights must be a vector")
	# check censor indicator
	if(is.vector(censor,mode="numeric")){
		if(is.null(times))stop("censor must be a matrix")
		if(length(censor)!=dim(y)[2])
			stop("censor must be the same length as the number of variables")
		censor <- rbind(matrix(1,ncol=dim(y)[2],nrow=dim(y)[1]-1),censor)}
	else if(is.matrix(censor)){
		if(any(dim(censor)!=dim(y)))stop("censor and response must have the same dimensions")}
	else if(!is.null(censor))stop("censor must be a vector or matrix")
	# check totals
	if(is.vector(totals,mode="numeric")){
		if(length(totals)!=dim(y)[2])
			stop("totals must be the same length as the number of variables")
		totals <- matrix(rep(totals,dim(y)[1]),ncol=dim(y)[2],byrow=TRUE)}
	else if(is.matrix(totals)){
		if(any(dim(totals)!=dim(y)))stop("totals and response must have the same dimensions")}
	else if(!is.null(totals)) stop("totals must be a vector or matrix")
	# check delta
	if(is.vector(delta,mode="numeric")){
		if(length(delta)!=dim(y)[2]){
			if(length(delta)==1)
				delta <- matrix(delta,nrow=dim(y)[1],ncol=dim(y)[2])
			else if(length(delta)==dim(y)[2])
				delta <- matrix(rep(delta,dim(y)[1]),ncol=dim(y)[2],byrow=TRUE)
			else stop("delta must be the same length as the number of variables")}}
	else if(is.matrix(delta)){
		if(any(dim(delta)!=dim(y)))stop("delta and response must have the same dimensions")}
	else if(!is.null(delta))stop("delta must be a scalar, vector, or matrix")}
else if(is.matrix(response)||is.data.frame(response)){
#
# one matrix or dataframe with independent observations or several time
#   series supplied
#
	# transform to a matrix
	if(is.data.frame(response))response <- as.matrix(response)
	if(is.data.frame(totals))totals <- as.matrix(totals)
	if(is.data.frame(delta))delta <- as.matrix(delta)
	# create vector of observations/individual
	nobs <- rep(dim(response)[2],dim(response)[1])
	# check times
	if(is.null(times)){
		if(is.null(censor)&&ttime)
			times <- as.double(rep(1:dim(response)[2],dim(response)[1]))}
	else if(is.matrix(times)){
		if(any(dim(times)!=dim(response)))
			stop("times matrix must have the same dimensions as response")
		# time steps can be 0 but not negative
		for(i in 1:dim(response)[1])
			if(any(diff(times[i,])<0,na.rm=TRUE))
			stop(paste("negative time step for individual ",i))
		times <- as.vector(t(times))}
	else if(is.vector(times,mode="numeric")) {
		if(is.null(nest)&&any(diff(times)<0,na.rm=TRUE))
			stop("times must be increasing")
		if(length(times)!=dim(response)[2])
			stop("number of times must equal number of response columns")
		times <- rep(times,dim(response)[1])}
	else stop("times must be a vector or matrix")
	# check weights
	if(is.matrix(weights)){
		if(any(dim(weights)!=dim(response)))
			stop("weights matrix must have the same dimensions as response")
		else weights <- as.vector(t(weights))}
	else if(is.vector(weights,mode="numeric")){
		if(length(weights)!=dim(response)[1])
			stop("weights vector must have same length as number of individuals")
		else weights <- rep(weights,rep(dim(response)[2],dim(response)[1]))}
	else if(!is.null(weights))stop("weights must be a vector or matrix")
	# check nesting
	if(is.matrix(nest)){
		if(any(dim(nest)!=dim(response)))
			stop("nest matrix must have the same dimensions as response")
		for(i in 1:dim(nest)[1])
			if(any(diff(nest[i,])!=0&diff(nest[i,])!=1,na.rm=TRUE))
				stop("nest categories must be consecutive increasing integers")
		tnest <- as.vector(t(nest))}
	else if(is.vector(nest,mode="numeric")){
		if(length(nest)!=dim(response)[2])
			stop("nest vector must have same length as number of individuals")
		if(any(diff(nest)!=0&diff(nest)!=1,na.rm=TRUE))
			stop("nest categories must be consecutive increasing integers")
		tnest <- rep(nest,dim(response)[1])}
	else if(!is.null(nest))stop("nest must be a vector or matrix")
	# check censor indicator
	if(is.matrix(censor)){
		if(any(dim(censor)!=dim(response)))
			stop("censor matrix must have the same dimensions as response")
		censor <- as.vector(t(censor))}
	else if(is.vector(censor,mode="numeric")){
	# if a vector, corresponds to last observation of each subject
		if(length(censor)!=dim(response)[1])
			stop("censor must be the same length as the number of individuals")
		else {
			tmp <- matrix(1,nrow=dim(response)[1],ncol=dim(response)[2])
			tmp[,dim(tmp)[2]] <- censor
			censor <- tmp}}
	else if(!is.null(censor))stop("censor must be a vector or matrix")
	# check totals
	if(is.matrix(totals)){
		if(any(dim(totals)!=dim(response)))
			stop("totals matrix must have the same dimensions as response")
		totals <- as.vector(t(totals))}
	else if(is.vector(totals,mode="numeric")){
		if(length(totals)!=dim(response)[1])
			stop("totals vector must have same length as number of individuals")
		else totals <- rep(totals,rep(dim(response)[2],dim(response)[1]))}
	else if(!is.null(totals))stop("totals must be a vector or matrix")
	# check delta
	if(is.matrix(delta)){
		if(any(dim(delta)!=dim(response)))
			stop("delta matrix must have the same dimensions as response")
		delta <- as.vector(t(delta))}
	else if(is.vector(delta,mode="numeric")){
		if(length(delta)>1){
			if(length(delta)!=dim(response)[2])
				stop("delta vector must have same length as number of individuals")
			else delta <- rep(delta,dim(response)[1])}}
	else if(!is.null(delta))stop("delta must be a vector or matrix")
	y <- as.vector(t(response))}
else if(mvr&&is.list(response)){
#
# a list of unbalanced multivariate repeated measurements supplied
#
	# obtain responses and possibly times
	y <- times <- nobs <- NULL
	nind <- 0
	nmv <- dim(as.matrix(response[[1]]))[2]
	for(i in response){
		nind <- nind+1
		if(!is.matrix(i))stop("response must be a list of matrices")
		nobs <- c(nobs,dim(i)[1])
		if(dim(i)[2]!=nmv)
			stop("all matrices must have the same number of columns")
		if(ttime){
			y <- rbind(y,i[,1:(nmv-1)])
			if(is.null(nest)&&any(diff(i[,nmv])<0,na.rm=TRUE))
				stop(paste("negative time step for individual ",nind))
			times <- c(times,i[,nmv])}
		else y <- rbind(y,i)}
	if(ttime)nmv <- nmv-1
	if(!is.null(nest)){
	# obtain nesting
		nind <- 0
		nes <- NULL
		if(!is.list(nest))stop("nest must be a list")
		for(i in nest){
			if(!is.vector(i,mode="numeric")&&!(is.matrix(i)&&dim(i)[2]==1))
				stop("nest must be a list of vectors")
			if(any(diff(i)!=0&diff(i)!=1,na.rm=TRUE))
				stop("nest categories must be consecutive increasing integers")
			nind <- nind+1
			if(length(i)!=nobs[nind])
				stop(paste("nest for individual",nind,"should have length",nobs[nind]))
			nes <- c(nes,i)}
		tnest <- nes
		rm(nes)}
	if(!is.null(weights)){
	# obtain weights
		nind <- 0
		wt <- NULL
		if(!is.list(weights))stop("weights must be a list")
		for(i in weights){
			if(!is.vector(i,mode="numeric")&&!is.vector(i,mode="logical")&&!(is.matrix(i)&&dim(i)[2]==1))
				stop("weights must be a list of vectors")
			nind <- nind+1
			if(length(i)!=nobs[nind])
				stop(paste("weights for individual",nind,"should have length",nobs[nind]))
			wt <- c(wt,i)}
		weights <- wt
		rm(wt)}
	if(!is.null(censor)){
	# obtain censoring
		nind <- 0
		cen <- NULL
		if(!is.list(censor))stop("censor must be a list")
		for(i in censor){
			if(!is.matrix(i))
				stop("censor must be a list of matrices")
			nind <- nind+1
			if(any(dim(i)!=c(nobs[nind],nmv)))
				stop(paste("censor for individual",nind,"should be",nobs[nind],"x",nmv,"matrix"))
			cen <- rbind(cen,i)}
		censor <- cen
		rm(cen)}
	if(!is.null(totals)){
	# obtain totals
		nind <- 0
		tot <- NULL
		if(!is.list(totals))stop("totals must be a list")
		for(i in totals){
			if(!is.matrix(i))
				stop("totals must be a list of matrices")
			nind <- nind+1
			if(any(dim(i)!=c(nobs[nind],nmv)))
				stop(paste("totals for individual",nind,"should be",nobs[nind],"x",nmv,"matrix"))
			tot <- rbind(tot,i)}
		totals <- tot
		rm(tot)}
	if(!is.null(delta)){
	# obtain delta
		nind <- 0
		del <- NULL
		if(!is.list(delta))stop("delta must be a list")
		for(i in delta){
			if(!is.matrix(i))
				stop("delta must be a list of matrices")
			nind <- nind+1
			if(any(dim(i)!=c(nobs[nind],nmv)))
				stop(paste("delta for individual",nind,"should be",nobs[nind],"x",nmv,"matrix"))
			del <- rbind(del,i)}
		delta <- del
		rm(del)}}
else if(is.list(response)){
#
# a list of unbalanced repeated measurements supplied
#
	# check if nest, delta, and/or totals are supplied
	# separately
	delv <- !is.null(delta)
	totv <- !is.null(totals)
	nestv <- !is.null(nest)
	if(is.null(censor)){
		# initialize
		times <- NULL
		tot <- del <- cen <- nes <- 0
		ncols <- dim(as.matrix(response[[1]]))[2]
		nc <- ttime+1
		if(ncols<nc)stop("matrices must have at least 2 columns: responses and times")
		else if(ncols>nc)for(j in response){
			# find columns for censor, totals, delta, nest
			j <- as.matrix(j)
			for(k in (nc+1):ncols){
				if(any(j[,k]<=0,na.rm=TRUE))cen <- k
				else if(any(j[,k]>1,na.rm=TRUE)&&all(j[,k]==trunc(j[,k]),na.rm=TRUE)){
					if(all(j[,1]>=0,na.rm=TRUE)&&all(j[,1]==trunc(j[,1]),na.rm=TRUE)&&all(j[,k]>=j[,1],na.rm=TRUE)&&any(diff(j[,k])<0,na.rm=TRUE)&&!totv)tot <- k
					else if(all(diff(j[,k])==0|diff(j[,k])==1,na.rm=TRUE)&&!nestv)nes <- k
					else stop(paste("column",k,"of unknown type"))}
				else if(!delv&&all(j[,k]>0,na.rm=TRUE))del <- k}
			if((((ncols==2&&!ttime)||ncols==3)&&(nes>0||cen>0||del>0||tot>0))||(((ncols==3&&!ttime)||ncols==4)&&((nes>0&&cen>0)||(nes>0&&del>0)||(nes>0&&tot>0)||(cen>0&&del>0)))||(((ncols>=4&&!ttime)||ncols>=5)&&((nes>0&&cen>0&&del>0)||(nes>0&&tot>0))))break}
		for(i in response){
			# obtain responses and times
			i <- as.matrix(i)
			nind <- nind+1
			if(dim(i)[2]!=ncols)
				stop(paste("Individual ",nind,"does not have a",ncols,"column matrix"))
			if(!nestv&&nes==0&&ttime&&any(diff(i[,2])<0,na.rm=TRUE))
				stop(paste("negative time step for individual ",nind))
			nobs <- c(nobs,dim(i)[1])
			y <- c(y,i[,1])
			if(ttime)times <- c(times,i[,2])
			# obtain censor, totals, delta, nest
			# from their columns
			if(nes>0){
				if(any(diff(i[,nes])!=0&diff(i[,nes])!=1,na.rm=TRUE))
					stop("nest categories for individual ",nind,"are not consecutive increasing integers")
				tnest <- c(tnest,i[,nes])}
			if(!totv&&tot>0)totals <- c(totals,i[,tot])
			if(cen>0)censor <- c(censor,i[,cen])
			if(!delv&&del>0)delta <- c(delta,i[,del])}}
	else if(is.vector(censor,mode="numeric")){
		# initialize (cannot be totals and censor available)
		del <- nes <- 0
		ncols <- dim(as.matrix(response[[1]]))[2]
		if(ncols>1){
			for(j in response){
			# find columns for delta, nest
				j <- as.matrix(j)
				for(k in 2:ncols){
					if(is.null(censor)&&any(j[,k]<=0,na.rm=TRUE))cen <- k
					else if(any(j[,k]>1,na.rm=TRUE)&&all(j[,k]==trunc(j[,k]),na.rm=TRUE))nes <- k
					else if(is.null(delta)&&all(j[,k]>0,na.rm=TRUE))del <- k}
				if((ncols==3&&(nes>0||cen>0||del>0))||(ncols==4&&((nes>0&&cen>0)||(nes>0&&del>0)||(cen>0&&del>0)))||(ncols>=5&&((nes>0&&cen>0&&del>0))))break}
			tmp <- NULL
			j <- 0
			for(i in response){
			# obtain responses
				i <- as.matrix(i)
				nind <- nind+1
				if(dim(i)[2]!=ncols)stop(paste("Individual ",nind,"does not have a",ncols,"column matrix"))
				nobs <- c(nobs,dim(i)[1])
				y <- c(y,i[,1])
				# construct censor
				tmp <- c(tmp,rep(1,dim(i)[1]-1),censor[j <- j+1])
				# obtain delta, nest from their columns
				if(nes>0){
					if(any(diff(i[,nes])!=0&diff(i[,nes])!=1,na.rm=TRUE))
					stop("nest categories for individual ",nind,"are not consecutive increasing integers")
					tnest <- c(tnest,i[,nes])}
				if(del>0)delta <- c(delta,i[,del])}
			censor <- tmp}
		else {
			tmp <- NULL
			j <- 0
			for(i in response){
			# obtain responses
				nind <- nind+1
				if(!is.vector(i,mode="numeric")&&!(is.matrix(i)&&dim(i)[2]==1))
					stop(paste("Individual ",nind,"does not have a vector or one column matrix"))
				# construct censor
				tmp <- c(tmp,rep(1,length(i)-1),censor[j <- j+1])
				y <- c(y,i)
				nobs <- c(nobs,length(i))}
			censor <- tmp}}
	else stop("If response is a list, censor must be a vector")
	if(nestv){
	# obtain nesting
		nind <- 0
		nes <- NULL
		if(!is.list(nest))stop("nest must be a list")
		for(i in nest){
			if(!is.vector(i,mode="numeric")&&!(is.matrix(i)&&dim(i)[2]==1))
				stop("nest must be a list of vectors")
			if(any(diff(i)!=0&diff(i)!=1,na.rm=TRUE))
				stop("nest categories must be consecutive increasing integers")
			nind <- nind+1
			if(length(i)!=nobs[nind])
				stop(paste("nest for individual",nind,"should have length",nobs[nind]))
			nes <- c(nes,i)}
		tnest <- nes
		rm(nes)}
	if(totv){
	# obtain totals
		nind <- 0
		tot <- NULL
		if(!is.list(totals))stop("totals must be a list")
		for(i in totals){
			if(!is.vector(i,mode="numeric")&&!(is.matrix(i)&&dim(i)[2]==1))
				stop("totals must be a list of vectors")
			nind <- nind+1
			if(length(i)!=nobs[nind])
				stop(paste("totals for individual",nind,"should have length",nobs[nind]))
			tot <- rbind(tot,i)}
		totals <- tot
		rm(tot)}
	if(delv){
	# obtain delta
		if(is.vector(delta)&&length(delta)==1)
			delta <-  rep(delta,length(y))
		else {
			nind <- 0
			del <- NULL
			if(!is.list(delta))stop("delta must be a list")
			for(i in delta){
				if(!is.vector(i,mode="numeric")&&!(is.matrix(i)&&dim(i)[2]==1))
					stop("delta must be a list of vectors")
				nind <- nind+1
				if(length(i)!=nobs[nind])
					stop(paste("delta for individual",nind,"should have length",nobs[nind]))
				del <- c(del,i)}
			delta <- del
			rm(del)}}
	if(!is.null(weights)){
	# obtain weights
		nind <- 0
		wt <- NULL
		if(!is.list(weights))stop("weights must be a list")
		for(i in weights){
			if(!is.vector(i,mode="numeric")&&!is.vector(i,mode="logical")&&!(is.matrix(i)&&dim(i)[2]==1))
				stop("weights must be a list of vectors")
			nind <- nind+1
			if(length(i)!=nobs[nind])
				stop(paste("weights for individual",nind,"should have length",nobs[nind]))
			wt <- c(wt,i)}
		weights <- wt
		rm(wt)}
	# check that totals, delta, and weights are now
	# correct if supplied separately
	if(totv){
		if(length(totals)==1)totals <- rep(totals,length(y))
		else if(length(totals)==length(nobs))
			totals <- totals[rep(1:length(nobs),nobs)]
		else if(length(totals)!=length(y))
			stop("totals must have one value per response")}
	if(delv&&length(delta)>1&&length(delta)!=length(y))
		stop("delta must have one value per response")
	if(!is.null(weights)&&length(y)!=length(weights))stop("weights must have one value per response")}
else stop("Responses must be supplied as a vector, matrix, dataframe, array, or list of matrices")
#
# make sure that the response is a matrix
#
if(!is.numeric(y))stop("response must be numeric")
if(is.matrix(y)){
	if(is.null(colnames(y)))colnames(y) <- if(length(names)==1)
		paste(names,1:dim(y)[2],sep="")
		else if(length(names)==dim(y)[2]) names
		else stop("incorrect number of names")}
else {
	y <- matrix(y,ncol=1)
	colnames(y) <- if(length(names)==1)names else "y"}
rownames(y) <- 1:dim(y)[1]
if(!is.null(units)){
	if(!is.character(units))stop("units must be a character vector")
	if(length(units)!=dim(y)[2])
		stop("units must be given for all responses")}
#
# check that type has the right length
#
if(is.null(type))type <- rep("unknown",dim(y)[2])
else {
	if(length(type)!=dim(y)[2])
		stop("a type must be supplied for each response")
	if(length(type)==1)type <- rep(type,dim(y)[2])
	if(any(is.na(type)))type[is.na(type)] <- "unknown"}
if(!is.null(censor)){
#
# check that censor has correct values
#
	if(!is.numeric(censor))stop("censor must be numeric")
	if(any(censor!=-1&censor!=0&censor!=1,na.rm=TRUE))
		stop("censor must only contain -1, 0, and 1")
	if(!is.null(censor)&&!is.matrix(censor))censor <- matrix(censor,ncol=1)
	# construct (cumulative) times from responses if univariate
	if(!mvr&&length(nobs)>1&&is.null(times)&&type=="duration"){
		j <- 1
		na <- is.na(y[,1])
		y[na,1] <- 0
		for(i in 1:length(nobs)){
			times <- c(times,cumsum(y[j:(j+nobs[i]-1),1]))
			j <- j+nobs[i]}
		y[na,1] <- NA}
	for(i in 1:dim(y)[2])
		if(type[i]=="unknown"&&any(!is.na(censor[,i])))
			type[i] <- "duration"
	# remove censor if unnecessary
	if(all(censor==1,na.rm=TRUE))censor <- NULL}
if(!is.null(totals)){
#
# check that totals has correct values
#
	if(!is.numeric(totals))stop("totals must be numeric")
	if(!is.matrix(totals))totals <- matrix(totals,ncol=1)
	for(i in 1:dim(y)[2])if(any(!is.na(totals[,i]))){
		if(any(y[,i]<0,na.rm=TRUE))
			stop("all responses must be non-negative for binomial data")
		if(any(totals[,i]<y[,i],na.rm=TRUE)||any(totals[,i]<0,na.rm=TRUE))
			stop("all totals must be non-negative and >= to responses")
		if(type[i]=="unknown"&&any(!is.na(totals[,i])))
			type[i] <- "nominal"}}
#
# check that nest, delta, weights have correct values
#
if(!is.null(tnest)){
	if(!is.numeric(tnest))stop("tnest must be numeric")
	if((any(tnest<1,na.rm=TRUE)||any(tnest!=trunc(tnest),na.rm=TRUE)))
		stop("nest must contain integers starting at 1")}
if(!is.null(delta)){
	if(!is.numeric(delta))stop("delta must be numeric")
	if(any(delta<=0,na.rm=TRUE))stop("delta must be strictly positive")
	if(!is.matrix(delta))delta <- matrix(delta,ncol=1)
	for(i in 1:dim(y)[2])
		if(type[i]=="unknown"&&any(!is.na(delta[,i])))
			type[i] <- "continuous"}
if(!is.null(weights)){
	if(!is.numeric(weights)&&!is.logical(weights))stop("weights must be numeric or logical")
	if(any(weights<0,na.rm=TRUE))stop("weights must be non-negative")}
#
# check that ordinal data have correct values
#
if(!is.na(match("ordinal",type))){
	for(i in 1:dim(y)[2])if(!is.na(match("ordinal",type[i]))){
		if(min(y[,i],na.rm=TRUE)!=0)
			stop("ordinal responses must be indexed from zero")
		if(any(as.integer(y[!is.na(y[,i]),i])!=y[!is.na(y[,i]),i]))
			stop("ordinal responses must be integers")}}
#
# combine with old object, if provided
#
if(!is.null(oldresponse)){
	if(any(nobs!=oldresponse$nobs))
		stop("old and new objects do not have the same number of observations per individual")
	if(dim(y)[1]!=dim(oldresponse$y)[1])
		stop("old and new objects do not have the same number of observations")
	if((!is.null(times)&&(is.null(oldresponse$times)||any(times!=oldresponse$times,na.rm=TRUE)))||(is.null(times)&&!is.null(oldresponse$times)))
		stop("old and new objects do not have the same times")
	if((!is.null(tnest)&&(is.null(oldresponse$tnest)||any(tnest!=oldresponse$tnest,na.rm=TRUE)))||(is.null(tnest)&&!is.null(oldresponse$tnest)))
		stop("old and new objects do not have the same nesting")
	if((!is.null(weights)&&(is.null(oldresponse$wt)||any(weights!=oldresponse$wt,na.rm=TRUE)))||(is.null(weights)&&!is.null(oldresponse$wt)))
		stop("old and new objects do not have the same weights")
	y <- cbind(oldresponse$y,y)
	if(!is.null(censor)){
		if(is.null(oldresponse$censor))
			censor <- cbind(matrix(NA,nrow=dim(oldresponse$y)[1],ncol=dim(oldresponse$y)[2]),censor)
		else censor <- cbind(oldresponse$censor,censor)}
	else if(!is.null(oldresponse$censor))
		censor <- cbind(oldresponse$censor,matrix(NA,nrow=dim(y)[1],ncol=dim(y)[2]))
	if(!is.null(totals)){
		if(is.null(oldresponse$n))
			totals <- cbind(matrix(NA,nrow=dim(oldresponse$y)[1],ncol=dim(oldresponse$y)[2]),totals)
		else totals <- cbind(oldresponse$n,totals)}
	else if(!is.null(oldresponse$n))
		totals <- cbind(oldresponse$n,matrix(NA,nrow=dim(y)[1],ncol=dim(y)[2]))
	if(!is.null(delta)){
		if(is.null(oldresponse$delta))
			delta <- cbind(matrix(1,nrow=dim(oldresponse$y)[1],ncol=dim(oldresponse$y)[2]),delta)
		else delta <- cbind(oldresponse$delta,delta)}
	else if(!is.null(oldresponse$delta))
		delta <- cbind(oldresponse$delta,matrix(1,nrow=dim(y)[1],ncol=dim(y)[2]))
	if(!is.null(units)){
		if(is.null(oldresponse$units))
			units <- c(rep(NA,dim(oldresponse$y)[2]),units)
		else units <- c(oldresponse$units,units)}
	else if(!is.null(oldresponse$units))
		units <- c(oldresponse$units,rep(NA,dim(y)[2]))
	type <- c(oldresponse$type,type)}
#
# put names on matrices
#
if(!is.null(totals)&&is.null(colnames(totals)))colnames(totals) <- colnames(y)
if(!is.null(censor)&&is.null(colnames(censor)))colnames(censor) <- colnames(y)
if(!is.null(delta)&&is.null(colnames(delta)))colnames(delta) <- colnames(y)
if(!is.null(units))names(units) <- colnames(y)
names(type) <- colnames(y)
#
# check for variable descriptions
#
if(!is.null(description)){
	if(!is.list(description))stop("description must be a list")
	if(!all(tmp <- names(description)%in%colnames(y)))
		stop(paste("variable(s)",names(description)[!tmp],"not found"))
	for(i in description)if(!is.character(i))
		stop("description list must contain character vectors")
	if(!is.null(oldresponse))
		description <- c(oldresponse$description,description)}
z <- list(y=y, nobs=nobs, times=times, nest=tnest, censor=censor, n=totals,
	coordinates=coordinates, wt=weights, delta=delta, units=units,
	type=type, description=description)
class(z) <- "response"
z}

### function to create a time-constant covariate (tccov) object
###
tcctomat <- function(ccov, names=NULL, units=NULL, oldccov=NULL,
	dataframe=TRUE, description=NULL){
if(inherits(ccov,"tccov")&&inherits(oldccov,"tccov")){
#
# check for compatibility
#
	if(dim(ccov$ccov)[1]!=dim(oldccov$ccov)[1])
		stop("incompatible tccov objects")
	if(!is.null(oldccov$units)||!is.null(ccov$units)){
		if(is.null(oldccov$units))
			oldccov$units <- rep(NA,dim(oldccov$ccov)[2])
		if(is.null(ccov$units))ccov$units <- rep(NA,dim(ccov$ccov)[2])
		oldccov$units <- c(oldccov$units,ccov$units)}
	oldccov$ccov <- cbind(oldccov$ccov,ccov$ccov)
	oldccov$linear <- NULL
	return(oldccov)}
linear <- NULL
if(is.language(ccov)){
#
# if provided as a formula, transform to a matrix
#
	linear <- ccov
	mt <- terms(ccov)
	mf <- model.frame(mt,parent.frame(),na.action=NULL)
	ccov <- model.matrix(mt,mf)[,-1,drop=FALSE]}
else if(is.factor(ccov)||is.vector(ccov,mode="character")){
#
# if provided as factor variables, make a dataframe
#
	if(is.null(names))names <- paste(deparse(substitute(ccov)))
	ccov <- data.frame(ccov)
	colnames(ccov) <- names}
if(is.vector(ccov,mode="numeric")){
#
# if a vector, get a name
#
	if(is.null(names))names <- paste(deparse(substitute(ccov)))
	ccov <- matrix(ccov,ncol=1)}
else if(is.data.frame(ccov)){
	if(!dataframe){
	# if a dataframe supplied, but should not be stored as one
                rm(names)
                units2 <- mt <- tmp3 <- tmp <- NULL
                j <- 0
                for(i in ccov){
                	j <- j+1
                	if(is.vector(i,mode="numeric")){
			# handle numeric vectors
                		tmp2 <- as.matrix(i)
				units2 <- c(units2,units[j])
                		colnames(tmp2) <- names(ccov)[j]}
                	else {
			# handle factor variables
                		mt <- terms(~i)
                		tmp2 <- model.matrix(mt,model.frame(mt,na.action=NULL))[,-1,drop=FALSE]
				units2 <- c(units2,rep(units[j],length(levels(i)[-1])))
				tmp3 <- dimnames(get(getOption("contrasts")[[if(is.ordered(i))2 else 1]])(levels(i),contrasts =TRUE))[[2]]
				if(is.null(tmp3))tmp3 <- 1:(length(levels(i))-1)
                		colnames(tmp2) <- paste(names(ccov)[j],tmp3,sep="")}
#                		colnames(tmp2) <- paste(names(ccov)[j],levels(i)[-1],sep="")}
                	tmp <- cbind(tmp,tmp2)}
		units <- units2
                ccov <- tmp
                rm(tmp,tmp2,tmp3,mt)}}
else if(!is.matrix(ccov))
	stop("Inter-unit (time-constant) covariates must be a vector, matrix, dataframe, or model formula")
if(is.null(colnames(ccov))){
#
# create names if not available
#
	if(is.null(names))names <- paste(deparse(substitute(ccov)))
	if(length(names)==1&&dim(ccov)[2]>1)
		names <- paste(names,1:dim(ccov)[2],sep="")
	colnames(ccov) <- names}
#
# check units
#
if(!is.null(units)){
	if(!is.character(units))stop("units must be a character vector")
	if(length(units)!=dim(ccov)[2])
		stop("units must be supplied for all covariates")}
#
# check for variable descriptions
#
if(!is.null(description)){
	if(!is.list(description))stop("description must be a list")
	if(!all(tmp <- names(description)%in%colnames(ccov)))
		stop(paste("variable(s)",names(description)[!tmp],"not found"))
	for(i in description)if(!is.character(i))
		stop("description list must contain character vectors")}
if(!is.null(oldccov)){
#
# combine new data with old data when available
#
	if(!inherits(oldccov,"tccov"))
		stop("oldccov must have class, tccov")
	oldccov$description <- c(oldccov$description,description)
	if(!is.null(oldccov$units)||!is.null(units)){
		if(is.null(oldccov$units))
			oldccov$units <- rep(NA,dim(oldccov$ccov)[2])
		if(is.null(units))units <- rep(NA,dim(ccov)[2])
		oldccov$units <- c(oldccov$units,units)}
	else if(dim(oldccov$ccov)[1]==dim(ccov)[1]){
		if(dataframe)oldccov$ccov <- data.frame(oldccov$ccov,ccov)
		else oldccov$ccov <- cbind(oldccov$ccov,ccov)}
	else stop("old and new covariates do not have the same number of individuals")}
else {
	if(dataframe)ccov <- as.data.frame(ccov)
	oldccov <- list(ccov=ccov,linear=linear,units=units,description=description)
	class(oldccov) <- "tccov"}
if(!is.null(oldccov$units))names(oldccov$units) <- colnames(oldccov$ccov)
if(is.data.frame(oldccov$ccov)){
#
# if no factor variables, store as a matrix anyway
#
	fac <- FALSE
	for(i in 1:dim(oldccov$ccov)[2])if(!is.vector(oldccov$ccov[,i],mode="numeric")){
		fac <- TRUE
		break}
	if(!fac)oldccov$ccov <- as.matrix(oldccov$ccov)}
oldccov}

### function to create a time-varying covariate (tvcov) object
###
tvctomat <- function(tvcov, names=NULL, units=NULL, interaction=NULL,
	ccov=NULL, oldtvcov=NULL, dataframe=TRUE, description=NULL){
#
# check for compatibility
#
if(inherits(tvcov,"tvcov")&&inherits(oldtvcov,"tvcov")){
	if(length(tvcov$nobs)!=length(oldtvcov$nobs)||
		any(tvcov$nobs!=oldtvcov$nobs))
		stop("incompatible tvcov objects")
	if(!is.null(oldtvcov$units)||!is.null(tvcov$units)){
		if(is.null(oldtvcov$units))
			oldtvcov$units <- rep(NA,dim(oldtvcov$tvcov)[2])
		if(is.null(tvcov$units))
			tvcov$units <- rep(NA,dim(tvcov$tvcov)[2])
		oldtvcov$units <- c(oldtvcov$units,tvcov$units)}
	oldtvcov$tvcov <- cbind(oldtvcov$tvcov,tvcov$tvcov)
	return(oldtvcov)}
nbs <- tvcv <- NULL
if(is.data.frame(tvcov)){
	if(is.null(names))names <- paste(deparse(substitute(tvcov)))
	if(length(names)!=1)stop("too many names")
	if(dataframe){
	# make new one-column dataframe
		nbs <- rep(dim(tvcov)[2],dim(tvcov)[1])
		tvcv <- data.frame(as.character(as.vector(t(as.matrix(tvcov)))),stringsAsFactors=TRUE)##tvcv <- as.data.frame(as.vector(t(as.matrix(tvcov))))
		colnames(tvcv) <- names}
	# if factors, as.matrix transforms to character for next step
	else tvcov <- as.matrix(tvcov)}
if(is.matrix(tvcov)&&is.character(tvcov)){
	nbs <- rep(dim(tvcov)[2],dim(tvcov)[1])
	if(is.null(names))names <- paste(deparse(substitute(tvcov)))
	if(length(names)!=1)stop("too many names")
	tvcv <- as.factor(as.vector(t(tvcov)))
	if(dataframe){
	# make new one-column dataframe
		tvcv <- as.data.frame(as.vector(t(as.matrix(tvcov))))
		colnames(tvcv) <- names}
	else {
	# make indicator matrix from factor
		mt <- terms(~tvcv)
		tmp3 <- dimnames(get(getOption("contrasts")[[if(is.ordered(tvcv))2 else 1]])(levels(tvcv),contrasts =TRUE))[[2]]
		if(is.null(tmp3))tmp3 <- 1:(length(levels(tvcv))-1)
		names <- paste(names,tmp3,sep="")
#		names <- paste(names,levels(tvcv)[-1],sep="")
		tvcv <- model.matrix(mt,model.frame(mt,na.action=NULL))[,-1,drop=FALSE]
		colnames(tvcv) <- names
		if(!is.null(units))units <- rep(units,dim(tvcv)[2])}}
else if(is.matrix(tvcov)){
#
# transform to a vector
#
	nbs <- rep(dim(tvcov)[2],dim(tvcov)[1])
	tvcv <- matrix(as.vector(t(tvcov)),ncol=1)
	if(!is.null(names)&&length(names)!=1)stop("too many names")
	colnames(tvcv) <- if(!is.null(names)) names
		else paste(deparse(substitute(tvcov)))}
else if(is.list(tvcov)&&!is.data.frame(tvcov)){
	if(inherits(tvcov,"tvcov")){
		nbs <- tvcov$nobs
		tvcv <- tvcov$tvcov}
	else {
		ncols <- dim(as.data.frame(tvcov[[1]]))[2]
		# create names
		if(is.null(names)){
			if(is.null(colnames(tvcov[[1]]))){
				names <- if(is.matrix(tvcov[[1]]))paste(paste(deparse(substitute(tvcov))),1:ncols,sep="")
				else paste(deparse(substitute(tvcov)))}
			else names <- colnames(tvcov[[1]])}
		# concatenate list elements into a matrix
		ff <- TRUE
		for(i in tvcov){
		# create one big dataframe
			i <- as.data.frame(i)
			if(dim(i)[2]!=ncols)
				stop("all elements of the list must have the same number of columns")
			nbs <- c(nbs,dim(i)[1])
			if(ff){
				tvcv <- i
				ff <- FALSE}
			else tvcv <- rbind(tvcv,i)}
		if(is.character(tvcv)||!dataframe){
		# if necessary, transform to indicator matrix
			tmp <- tmp2 <- mt <- NULL
			for(i in 1:ncols){
				if(is.numeric(tvcv[,i])){
					tmp <- cbind(tmp,tvcv[,i])
					tmp2 <- c(tmp2,names[i])}
				else {
					mt <- terms(~tvcv[,i])
					tmp <- cbind(tmp,model.matrix(mt,model.frame(mt,na.action=NULL))[,-1,drop=FALSE])
					tmp3 <- dimnames(get(getOption("contrasts")[[if(is.ordered(tvcv[,i]))2 else 1]])(levels(tvcv[,i]),contrasts =TRUE))[[2]]
					if(is.null(tmp3))tmp3 <- 1:(length(levels(tvcv[,i]))-1)
					tmp2 <- c(tmp2,paste(names[i],tmp3,sep=""))}}
#					tmp2 <- c(tmp2,paste(names[i],levels(as.factor(tvcv[,i]))[-1],sep=""))}}
			tvcv <- tmp
			names <- tmp2
			ncols <- length(names)
			rm(tmp,tmp2,mt)}
		# create colnames if necessary
		if(is.null(colnames(tvcov[[1]]))){
			if(is.null(names))names <- paste(deparse(substitute(tvcov)))}
		else if(length(names)!=ncols)names <- colnames(tvcov[[1]])
		if((length(names)==1&&ncols>1))
			names <- paste(names,1:ncols,sep="")
		if(length(names)!=ncols)
			stop(paste(ncols,"variable names required"))
		colnames(tvcv) <- names}}
else if(!is.data.frame(tvcov))
	stop("Intra-unit (time-varying) covariates must be a matrix, dataframe, or list")
if(!is.null(interaction)){
#
# if necessary, create interactions
#
	name <- colnames(tvcv)
	units <- tvcov$units
	if(is.character(interaction)){
	# if names supplied, find corresponding columns
		mat <- match(interaction,name)
		if(any(is.na(mat)))
			stop(paste("Intra-unit (time-varying) covariate(s)",ccov[is.na(mat)],"not found"))
		interaction <- mat}
	if(is.vector(interaction,mode="numeric")){
		if(length(interaction)>length(name))
			stop("too many interactions")
		if(!is.data.frame(tvcv))colnames(tvcv) <- NULL
		if(!is.null(ccov)){
		# if interactions with time-constant covariates
			if(inherits(ccov,"tccov")){
			  ## bruce swihart edit:
			  ## switch the next two lines to avoid
			  ## R CMD Check error
			  ## in examples of tvctomat.Rd
			  units2 <- ccov$units
			  ccov <- ccov$ccov
			  if(!is.null(units)&&is.null(units2))
					units2 <- rep("NA",dim(ccov)[2])
				if(is.null(units)&&!is.null(units2))
					units <- rep("NA",dim(tvcov$tvcov)[2])}
			if(!is.matrix(ccov)&&!is.data.frame(ccov)){
			# if a vector, transform to matrix
				tmp <- paste(deparse(substitute(ccov)))
				ccov <- matrix(ccov)
				colnames(ccov) <- tmp}
			if(dim(ccov)[1]!=length(nbs))
				stop("ccov does not have one observation per individual")
			# find desired covariates
			if(is.null(names))names <- colnames(ccov)
			mat <- match(names,colnames(ccov))
			if(any(is.na(mat)))stop(paste("covariates",names[is.na(mat)],"not found"))
			oldtvcov <- tvcv
			if(!is.data.frame(oldtvcov))colnames(oldtvcov) <- name
			if(!is.data.frame(oldtvcov)&&!is.data.frame(ccov)){
			# calculate interactions for ordinary matrices
				for(i in 1:length(interaction))for(j in 1:length(mat)){
					oldtvcov <- cbind(oldtvcov,tvcv[,interaction[i]]*rep(ccov[,mat[j]],nbs))
					name <-  c(name,paste(name[interaction[i]],".",names[j],sep=""))
					if(!is.null(units))units <- c(units,paste(units[interaction[i]],".",units2[j],sep=""))}}
			else {
			# calculate interactions when expansion required
				for(i in 1:length(interaction))
					for(j in 1:length(mat)){
					mt <- terms(~tvcv[,interaction[i]]:rep(ccov[,mat[j]],nbs))
					tmp <- model.matrix(mt,model.frame(mt,na.action=NULL))[,-1,drop=FALSE]
			                if(!is.vector(tvcv[,interaction[i]],mode="numeric")){
			                	if(!is.vector(ccov[,mat[j]],mode="numeric")){
			                		nam <- NULL
			                		tmp2 <- paste(name[interaction[i]],levels(tvcv[,interaction[i]])[-1],".",sep="")
			                		for(k in 1:length(levels(ccov[,mat[j]])[-1]))
			                		nam <- c(nam,paste(tmp2,names[j],levels(ccov[,mat[j]])[-1][k],sep=""))
			                		tmp <- tmp[,-c(1:length(levels(tvcv[,interaction[i]])),seq(1,length(levels(tvcv[,interaction[i]]))*length(levels(ccov[,mat[j]])),by=length(levels(tvcv[,interaction[i]])))),drop=FALSE]}
			                	else {
			                		nam <- paste(paste(name[interaction[i]],levels(tvcv[,interaction[i]])[-1],sep=""),".",names[j],sep="")
			                		tmp <- tmp[,-1,drop=FALSE]}
							if(!is.null(units))units <- c(units,rep(units2[j],length(levels(tvcv[,interaction[i]])[-1])))}
			                else {
			                	if(!is.vector(ccov[,mat[j]],mode="numeric")){
			                		nam <- paste(name[interaction[i]],".",paste(names[j],levels(ccov[,mat[j]])[-1],sep=""),sep="")
			                		tmp <- tmp[,-1,drop=FALSE]
							if(!is.null(units))units <- c(units,rep(units[interaction[i]],length(levels(ccov[,mat[j]])[-1])))}
			                	else {
							nam <- paste(name[interaction[i]],".",names[j],sep="")
							if(!is.null(units))units <- c(units,paste(units[interaction[i]],".",units2[j],sep=""))}}
			                colnames(tmp) <- nam
					name <- c(name,nam)
					oldtvcov <- cbind(oldtvcov,tmp)}}
			if(!is.data.frame(oldtvcov))colnames(oldtvcov) <- name
			oldtvcov <- list(tvcov=oldtvcov,nobs=nbs,units=units)}
		else if(length(interaction)==2){
		# one pair of interactions
			if(is.data.frame(tvcv)){
			# expand dataframe
				mt <- terms(~tvcv[,interaction[1]]:tvcv[,interaction[2]])
				tmp <- model.matrix(mt,model.frame(mt,na.action=NULL))[,-1,drop=FALSE]
				if(!is.vector(tvcv[,interaction[1]],mode="numeric")){
					if(!is.vector(tvcv[,interaction[2]],mode="numeric")){
						names <- NULL
						tmp2 <- paste(name[interaction[1]],levels(tvcv[,interaction[1]])[-1],".",sep="")
						for(i in 1:length(levels(tvcv[,interaction[2]])[-1]))
						names <- c(names,paste(tmp2,name[interaction[2]],levels(tvcv[,interaction[2]])[-1][i],sep=""))
						tmp <- tmp[,-c(1:length(levels(tvcv[,interaction[1]])),seq(1,length(levels(tvcv[,interaction[1]]))*length(levels(tvcv[,interaction[2]])),by=length(levels(tvcv[,interaction[1]])))),drop=FALSE]}
					else {
						names <- paste(paste(name[interaction[1]],levels(tvcv[,interaction[1]])[-1],sep=""),".",name[interaction[2]],sep="")
						tmp <- tmp[,-1,drop=FALSE]
						if(!is.null(units))units <- c(units,paste(rep(units[interaction[1]],length(levels(tvcv[,interaction[1]])[-1])),".",units[interaction[2]],sep=""))}}
				else {
					if(!is.vector(tvcv[,interaction[2]],mode="numeric")){
						names <- paste(name[interaction[1]],".",paste(name[interaction[2]],levels(tvcv[,interaction[2]])[-1],sep=""),sep="")
						tmp <- tmp[,-1,drop=FALSE]
						if(!is.null(units))units <- c(units,paste(units[interaction[1]],".",rep(units[interaction[2]],length(levels(tvcv[,interaction[2]])[-1])),sep=""))}
					else {
						names <- paste(name[interaction[1]],".",name[interaction[2]],sep="")
						if(!is.null(units))units <- c(units,paste(units[interaction[1]],".",units[interaction[2]],sep=""))}}
				colnames(tmp) <- names
				oldtvcov <- list(tvcov=cbind(tvcv,tmp),nobs=nbs,units=units)}
			else {
				units <- if(is.null(tvcov$units))NULL else c(tvcov$units,paste(tvcov$units[interaction[1]],".",tvcov$units[interaction[2]],sep=""))
				oldtvcov <- list(tvcov=cbind(tvcv,tvcv[,interaction[1]]*tvcv[,interaction[2]]),nobs=nbs,units=units)}
			if(!is.data.frame(oldtvcov$tvcov))
				colnames(oldtvcov$tvcov) <- c(name,paste(name[interaction[1]],".",name[interaction[2]],sep=""))}
		else stop("interaction must be a vector containing column numbers or variable names")
		class(oldtvcov) <- "tvcov"}}
else if(!is.null(oldtvcov)){
#
# check for variable descriptions
#
if(!is.null(description)){
	if(!is.list(description))stop("description must be a list")
	if(!all(tmp <- names(description)%in%colnames(tvcv)))
		stop(paste("variable(s)",names(description)[!tmp],"not found"))
	for(i in description)if(!is.character(i))
		stop("description list must contain character vectors")}
#
# if old tvcov, combine with new one
#
	if(!inherits(oldtvcov,"tvcov"))
		stop("oldtvcov must have class, tvcov")
	oldtvcov$description <- c(oldtvcov$description,description)
	if(!is.null(oldtvcov$units)||!is.null(units)){
		if(is.null(oldtvcov$units))
			oldtvcov$units <- rep(NA,dim(oldtvcov$tvcov)[2])
		if(is.null(units))units <- rep(NA,dim(tvcv)[2])
		oldtvcov$units <- c(oldtvcov$units,units)}
	if((dim(oldtvcov$tvcov)[1]==dim(tvcv)[1])&&all(oldtvcov$nobs==nbs)){
		if(dataframe)oldtvcov$tvcov <- data.frame(oldtvcov$tvcov,tvcv,stringsAsFactors = TRUE)
		else oldtvcov$tvcov <- cbind(oldtvcov$tvcov,tvcv)}
	else stop("old and new covariates do not have the same numbers of observations")}
else {
	# check units
	if(!is.null(units)){
		if(!is.character(units))
			stop("units must be a character vector")
		if(length(units)!=dim(tvcv)[2])
			stop("units must be supplied for all covariates")}
	if(dataframe)tvcv <- as.data.frame(tvcv)
	oldtvcov <- list(tvcov=tvcv,nobs=nbs,units=units,description=description)
	class(oldtvcov) <- "tvcov"}
if(!is.null(oldtvcov$units))names(oldtvcov$units) <- colnames(oldtvcov$tvcov)
#
# if no factor variables present, return a matrix anyway
#
if(is.data.frame(oldtvcov$tvcov)){
	fac <- FALSE
	for(i in 1:dim(oldtvcov$tvcov)[2])if(!is.vector(oldtvcov$tvcov[,i],mode="numeric")){
		fac <- TRUE
		break}
	if(!fac)oldtvcov$tvcov <- as.matrix(oldtvcov$tvcov)}
oldtvcov}

### functions to create a repeated object
###
### method to create repeated object removing NAs
###
rmna <- function(response, ccov=NULL, tvcov=NULL){
#
# if necessary, convert response
#
if(!inherits(response,"response"))response <- restovec(response)
#
# if necessary, expand nobs
#
if(length(response$nobs)==1&&response$nobs==1)
	response$nobs <- rep(1,length(response$y))
#
# if necessary, convert ccov
#
if(!is.null(ccov)){
	if(!inherits(ccov,"tccov"))ccov <- tcctomat(ccov)
	if(length(response$nobs)!=dim(ccov$ccov)[1])
		stop("Numbers of individuals for response and for inter-unit (time-constant) covariates do not agree.")}
#
# if necessary, convert tvcov
#
if(!is.null(tvcov)){
	if(!inherits(tvcov,"tvcov"))tvcov <- tvctomat(tvcov)
	if(length(response$nobs)!=length(tvcov$nobs)||
		any(response$nobs!=tvcov$nobs))
		stop("Numbers of observations for response and intra-unit (time-varying) covariates do not agree.")}
#
# create NA indicators
#
rna <- rep(TRUE,dim(response$y)[1])
for(i in 1:dim(response$y)[2])rna <- rna&!is.na(response$y[,i])
if(!is.null(response$times))rna <- rna&!is.na(response$times)
if(!is.null(response$nest))rna <- rna&!is.na(response$nest)
if(!is.null(response$wt))rna <- rna&!is.na(response$wt)
if(!is.null(response$coordinates))
	rna <- rna&!is.na(response$coordinates[,1])&!is.na(response$coordinates[,2])
if(!is.null(response$n)){
	for(i in 1:dim(response$y)[2])if(any(!is.na(response$n[,i])))
		rna <- rna&!is.na(response$n[,i])}
for(i in 1:length(response$nobs))
	if(!is.null(ccov)&&any(is.na(ccov$ccov[i,])))
		rna[covind(response)==i] <- FALSE
if(!is.null(tvcov))
	for(i in 1:dim(tvcov$tvcov)[2])rna <- rna&!is.na(tvcov$tvcov[,i])
#
# remove NAs
#
if(any(!rna)){
	# remove NAs from variables associated with response
        response$y <- response$y[rna,,drop=FALSE]
        if(!is.null(response$times))response$times <- response$times[rna]
        if(!is.null(response$nest))response$nest <- response$nest[rna]
        if(!is.null(response$wt))response$wt <- response$wt[rna]
        if(!is.null(response$coordinates))
        	response$coordinates <- response$coordinates[rna,]
        if(!is.null(response$n))response$n <- response$n[rna,,drop=FALSE]
        if(!is.null(response$censor)){
        	response$censor <- response$censor[rna,,drop=FALSE]
        	if(all(response$censor==1))response$censor <- NULL}
        if(!is.null(response$delta)&&length(response$delta)>1)
        	response$delta <- response$delta[rna,,drop=FALSE]
        if(!is.null(tvcov))tvcov$tvcov <- tvcov$tvcov[rna,,drop=FALSE]
        # correct nobs
        tmp <- NULL
        j <- c(0,cumsum(response$nobs))
        for(i in 1:length(response$nobs)){
        	tmp <- c(tmp,sum(rna[(j[i]+1):j[i+1]]))
        	if(tmp[i]==0)
        		warning(paste("Individual",i,"has no observations"))}
        response$nobs <- tmp[tmp>0]
        # remove NAs from ccov
        if(!is.null(ccov)){
        	ccov$ccov <- ccov$ccov[tmp>0,,drop=FALSE]
        	for(i in 1: dim(ccov$ccov)[2])
        		if(length(unique(ccov$ccov[,i]))==1)
        			warning(paste("covariate",colnames(ccov$ccov)[i],"has only one value\n"))}
        # remove NAs from tvcov
	if(!is.null(tvcov)){
		tvcov$nobs <- response$nobs
		for(i in 1: dim(tvcov$tvcov)[2])
			if(length(unique(tvcov$tvcov[,i]))==1)
			warning(paste("covariate",colnames(tvcov$tvcov)[i],"has only one value\n"))}}
#
# if independent observations, reset nobs
#
if(all(response$nobs==1))response$nobs <- 1
z <- list(response=response,tvcov=tvcov,ccov=ccov)
class(z) <- "repeated"
z}

### method to create repeated object leaving NAs
###
lvna <- function(response, ccov=NULL, tvcov=NULL){
#
# if necessary, convert response
#
if(!inherits(response,"response"))response <- restovec(response)
#
# if necessary, expand nobs
#
if(length(response$nobs)==1&&response$nobs==1)
	response$nobs <- rep(1,length(response$y))
#
# if necessary, convert ccov
#
if(!is.null(ccov)){
	if(!inherits(ccov,"tccov"))ccov <- tcctomat(ccov)
	if(length(response$nobs)!=dim(ccov$ccov)[1])
		stop("Numbers of individuals for response and for intra-unit (time-constant) covariates do not agree.")}
#
# if necessary, convert tvcov
#
if(!is.null(tvcov)){
	if(!inherits(tvcov,"tvcov"))tvcov <- tvctomat(tvcov)
	if(any(response$nobs!=tvcov$nobs))
		stop("Numbers of observations for response and intra-unit (time-varying) covariates do not agree.")}
#
# create NA indicators
#
rna <- rep(TRUE,dim(response$y)[1])
for(i in 1:dim(response$y)[2])rna <- rna&!is.na(response$y[,i])
if(!is.null(response$times))rna <- rna&!is.na(response$times)
if(!is.null(response$nest))rna <- rna&!is.na(response$nest)
if(!is.null(response$coordinates))
	rna <- rna&!is.na(response$coordinates[,1])&!is.na(response$coordinates[,2])
if(!is.null(response$n)){
	for(i in 1:dim(response$y)[2])if(any(!is.na(response$n[,i])))
		rna <- rna&!is.na(response$n[,i])}
for(i in 1:length(response$nobs))
	if(!is.null(ccov)&&any(is.na(ccov$ccov[i,])))rna[covind(response)==i] <- FALSE
if(!is.null(tvcov))
	for(i in 1:dim(tvcov$tvcov)[2])rna <- rna&!is.na(tvcov$tvcov[,i])
#
# if independent observations, reset nobs
#
if(all(response$nobs==1))response$nobs <- 1
z <- list(response=response,tvcov=tvcov,ccov=ccov,
	NAs=if(any(!rna))!rna else NULL)
class(z) <- "repeated"
z}

### method to create repeated object from a dataframe
###
dftorep <- function(dataframe, response, id=NULL, times=NULL, censor=NULL,
	totals=NULL, weights=NULL, nest=NULL, delta=NULL,
	coordinates=NULL, type=NULL, ccov=NULL, tvcov=NULL, na.rm=TRUE){
if(missing(dataframe)||!is.data.frame(dataframe))
	stop("a dataframe must be supplied")
if(missing(response)||!is.character(response))
	stop("name(s) of response variables must be supplied")
#
# find response information and construct object
#
cn <- colnames(dataframe)
nc <- match(response,cn)
if(any(is.na(nc)))stop(paste("response",response[is.na(nc)],"not found"))
tot <- matrix(NA,ncol=nc,nrow=dim(dataframe)[1])
for(i in nc)if(is.matrix(dataframe[[i]])&&dim(dataframe[[i]])[2]==2){
		tot[,i] <- dataframe[[i]][,1]+dataframe[[i]][,2]
		dataframe[[i]] <- dataframe[[i]][,1]}
if(all(is.na(tot)))tot <- NULL
if(!is.numeric(z <- as.matrix(dataframe[,nc,drop=FALSE])))
	stop("response must be numeric")
z <- list(response=list(y=z,nobs=NULL,times=NULL,nest=NULL,coordinates=NULL,
	censor=NULL,n=tot,wt=NULL,delta=NULL,units=NULL,type=NULL),
	ccov=NULL,tvcov=NULL)
class(z) <- "repeated"
class(z$response) <- "response"
tobs <- dim(z$response$y)[1]
nrcol <- dim(z$response$y)[2]
if(is.null(type))z$response$type <- rep("unknown",nrcol)
else if(length(type)!=nrcol)stop("a type must be supplied for each response")
else {
	for(i in 1:length(type))
		z$response$type[i] <- match.arg(type[i],
			c("nominal","ordinal","discrete","duration","continuous","unknown"))
	if(any(is.na(z$response$type)))
		z$response$type[is.na(z$response$type)] <- "unknown"}
rna <- rep(TRUE,tobs)
for(i in 1:nrcol)rna <- rna&!is.na(z$response$y[,i])
if(is.null(id))
	z$response$nobs <- if(is.null(times)) rep(1,tobs) else tobs
else {
	if(!is.character(id)||length(id)>1)
		stop("id must be the name of one variable")
	nc <- match(id,cn)
	if(is.na(nc))stop("id not found")
	id <- as.vector(dataframe[,nc])
	if(is.character(id)||is.factor(id))id <- as.numeric(as.factor(id))
	else if(any(diff(id)!=0&diff(id)!=1,na.rm=TRUE))
		warning("id not consecutively numbered")
	nobs <- table(id)
	z$response$nobs <- as.vector(nobs[match(unique(id),names(nobs))])}
if(any(z$response$nobs!=1)&&length(z$response$nobs)>1)for(i in unique(id)){
	if(any(diff((1:tobs)[id==i])>1,na.rm=TRUE))
		stop(paste("observations for individual",i,"not together in table"))}
if(!is.null(nest)){
	if(all(z$response$nobs==1))
		stop("these are not repeated measurements - nest not valid")
	if(!is.character(nest)||length(nest)>1)
		stop("nest must be the name of one variable")
	nc <- match(nest,cn)
	if(is.na(nc))stop("nest not found")
	z$response$nest <- as.vector(dataframe[,nc])
	if(is.character(z$response$nest))
		z$response$nest <- as.numeric(as.factor(z$response$nest))
	else if(!is.numeric(z$response$nest))stop("nest must be numeric")
	rna <- rna&!is.na(z$response$nest)}
if(!is.null(times)){
	if(!is.character(times)||length(times)>1)
		stop("times must be the name of one variable")
	nc <- match(times,cn)
	if(is.na(nc))stop("times not found")
	z$response$times <- as.vector(dataframe[,nc])
	if(!is.numeric(z$response$times))stop("times must be numeric")
	rna <- rna&!is.na(z$response$times)}
if(!is.null(times))for(i in unique(id))
	if(!is.null(nest))for(j in unique(z$response$nest)){
		if(any(diff(z$response$times[id==i&z$response$nest==j])<0,na.rm=TRUE))
			stop(paste("negative time step for individual",i))}
	else
		if(any(diff(z$response$times[id==i])<0,na.rm=TRUE))
			stop(paste("negative time step for individual",i))
if(!is.null(nest))for(i in unique(id))
	if(any(diff(z$response$nest[id==i])!=0&
		diff(z$response$nest[id==i])!=1,na.rm=TRUE))
		stop(paste("nest for individual",i,"not consecutively numbered"))
if(!is.null(censor)){
	if(!is.character(censor)||length(censor)!=nrcol)
		stop("censor must have one name per response variable")
	nc <- match(censor,cn)
	if(any(is.na(nc)))stop("censor",censor[is.na(nc)],"not found")
	z$response$censor <- as.matrix(dataframe[,nc,drop=FALSE])
	if(!is.numeric(z$response$censor))stop("censor must be numeric")
	if(any(z$response$censor!=1&z$response$censor!=0&
		z$response$censor!=-1,na.rm=TRUE))
		stop("censor indicator can only have values, -1, 0, 1")
	for(i in 1:nrcol)if(!all(is.na(z$response$censor[,i]))){
		rna <- rna&!is.na(z$response$censor[,i])
		if(z$response$type[i]=="unknown")
			z$response$type[i] <- "duration"}}
if(!is.null(totals)){
	if(!is.character(totals)||length(totals)!=nrcol)
		stop("totals must have one name per response variable")
	nc <- match(totals,cn)
	if(any(is.na(nc)))stop("totals",totals[is.na(nc)],"not found")
	z$response$n <- as.matrix(dataframe[,nc,drop=FALSE])
	if(!is.numeric(z$response$n))stop("totals must be numeric")
	if(any(z$response$y<0|z$response$n<z$response$y,na.rm=TRUE))
		stop("responses must lie between 0 and totals")
	for(i in 1:nrcol)if(!all(is.na(z$response$n[,i]))){
		rna <- rna&!is.na(z$response$n[,i])
		if(z$response$type[i]=="unknown")
			z$response$type[i] <- "nominal"}}
if(!is.null(delta)){
	if(is.numeric(delta)){
		if(length(delta)==1)
			z$response$delta <- matrix(delta,ncol=nrcol,nrow=tobs)
		else if(length(delta)==nrcol)
			z$response$delta <- matrix(rep(delta,tobs),ncol=nrcol,nrow=tobs,byrow=TRUE)
		else stop("delta must contain one value for each response")
		if(any(z$response$type=="unknown"))for(i in 1:nrcol)
			if(z$response$type[i]=="unknown")
				z$response$type[i] <- "continuous"}
	else {
		if(!is.character(delta)||length(delta)!=nrcol)
			stop("delta must have one name per response variable")
		nc <- match(delta,cn)
		if(any(is.na(nc)))stop("delta",delta[is.na(nc)],"not found")
		z$response$delta <- as.matrix(dataframe[,nc,drop=FALSE])
		if(!is.numeric(z$response$delta))stop("delta must be numeric")
		if(any(z$response$y<=0,na.rm=TRUE))
			stop("delta must be strictly positive")
		for(i in 1:nrcol)if(!all(is.na(z$response$delta[,i]))){
			rna <- rna&!is.na(z$response$delta[,i])
			if(z$response$type[i]=="unknown")
				z$response$type[i] <- "continuous"}}}
if(!is.null(weights)){
	if(!is.character(weights)||length(times)>1)
		stop("weights must be the name of one variable")
	nc <- match(weights,cn)
	if(is.na(nc))stop("weights not found")
	z$response$wt <- as.vector(dataframe[,nc])
	if(!is.numeric(z$response$wt))stop("weights must be numeric")
	rna <- rna&!is.na(z$response$wt)}
if(!is.null(coordinates)){
	if(!is.character(coordinates)||(length(coordinates)!=2&&
		length(coordinates)!=3))
		stop("coordinates must be the name of 2 or 3 variables")
	nc <- match(coordinates,cn)
	if(any(is.na(nc)))
		stop("coordinates",coordinates[is.na(nc)],"not found")
	z$response$coordinates <- as.matrix(dataframe[,nc,drop=FALSE])
	if(!is.numeric(z$response$coordinates))
		stop("coordinates must be numeric")
	for(i in 1:length(coordinates))
		rna <- rna&!is.na(z$response$coordinates[,i])}
#
# find time-varying covariates
#
if(!is.null(tvcov)){
	if(all(z$response$nobs==1))
		stop("these are not repeated measurements - tvcov not valid")
	z$tvcov <- list(tvcov=NULL,nobs=z$response$nobs)
	class(z$tvcov) <- "tvcov"
	nc <- match(tvcov,cn)
	if(any(is.na(nc)))stop("tvcov",tvcov[is.na(nc)],"not found")
	z$tvcov$tvcov <- dataframe[,nc,drop=FALSE]
	for(i in 1:length(tvcov))rna <- rna&!is.na(z$tvcov$tvcov[,i])
	# if no factor variables present, return a matrix anyway
	fac <- FALSE
	for(i in 1:dim(z$tvcov$tvcov)[2])
		if(!is.vector(z$tvcov$tvcov[,i],mode="numeric")){
		fac <- TRUE
		break}
	if(!fac)z$tvcov$tvcov <- as.matrix(z$tvcov$tvcov)}
#
# find time-constant covariates
#
if(!is.null(ccov)){
	z$ccov <- list(ccov=NULL)
	class(z$ccov) <- "tccov"
	nc <- match(ccov,cn)
	if(any(is.na(nc)))stop("ccov",ccov[is.na(nc)],"not found")
	z$ccov$ccov <- dataframe[,nc,drop=FALSE]
	for(i in unique(id))for(j in 1:length(ccov))
		if(sum(!is.na(unique(z$ccov$ccov[id==i,j])))>1)
		stop(paste("ccov",ccov[j],"for individual",i,"not constant"))
	for(i in 1:length(ccov))rna <- rna&!is.na(z$ccov$ccov[,i])
	j <- c(0,cumsum(z$response$nobs)[-length(z$response$nobs)])+1
	z$ccov$ccov <- z$ccov$ccov[j,,drop=FALSE]
	# if no factor variables present, return a matrix anyway
	fac <- FALSE
	for(i in 1:dim(z$ccov$ccov)[2])
		if(!is.vector(z$ccov$ccov[,i],mode="numeric")){
		fac <- TRUE
		break}
	if(!fac)z$ccov$ccov <- as.matrix(z$ccov$ccov)}
#
# remove NAs
#
if(na.rm&&any(!rna)){
	# remove NAs from variables associated with response
	z$response$y <- z$response$y[rna,,drop=FALSE]
	if(!is.null(z$response$times))z$response$times <- z$response$times[rna]
	if(!is.null(z$response$nest))z$response$nest <- z$response$nest[rna]
	if(!is.null(z$response$coordinates))
		z$response$coordinates <- z$response$coordinates[rna,]
	if(!is.null(z$response$n))z$response$n <- z$response$n[rna,,drop=FALSE]
	if(!is.null(z$response$censor)){
		z$response$censor <- z$response$censor[rna,,drop=FALSE]
		if(all(z$response$censor==1))z$response$censor <- NULL}
	if(!is.null(z$response$delta)&&length(z$response$delta)>1)
		z$response$delta <- z$response$delta[rna,,drop=FALSE]
	if(!is.null(z$tvcov))z$tvcov$tvcov <- z$tvcov$tvcov[rna,,drop=FALSE]
	# correct nobs
	tmp <- NULL
	j <- c(0,cumsum(z$response$nobs))
	for(i in 1:length(z$response$nobs)){
		tmp <- c(tmp,sum(rna[(j[i]+1):j[i+1]]))
		if(tmp[i]==0)
			warning(paste("Individual",i,"has no observations"))}
	z$response$nobs <- tmp[tmp>0]
	# remove NAs from ccov
	if(!is.null(z$ccov)){
		z$ccov$ccov <- z$ccov$ccov[tmp>0,,drop=FALSE]
		for(i in 1: dim(z$ccov$ccov)[2])
			if(length(unique(z$ccov$ccov[,i]))==1)
			warning(paste("covariate",colnames(z$ccov$ccov)[i],"has only one value\n"))}
	# remove NAs from tvcov
	if(!is.null(z$tvcov)){
		z$tvcov$nobs <- z$response$nobs
		for(i in 1: dim(z$tvcov$tvcov)[2])
			if(length(unique(z$tvcov$tvcov[,i]))==1)
			warning(paste("covariate",colnames(z$tvcov$tvcov)[i],"has only one value\n"))}}
if(!na.rm&&any(!rna))z$NAs <- !rna
#
# if independent observations, reset nobs
#
if(all(z$response$nobs==1))z$response$nobs <- 1
z}

### methods for objects created by these functions

### print methods
###
print.response <- function(x, nindmax=50, ...){
  z <- x; rm(x)
nobs <- nobs(z)
nind <- length(nobs)
cn <- colnames(z$y)
tmp <- rbind(colnames(z$y),z$type)
rntmp <- c(if(length(cn)>1)"Names:" else "Name: ","Type:")
if(!is.null(z$units)){
	tmp <- rbind(tmp,z$units)
	rntmp <- c(rntmp,"Units:")}
rownames(tmp) <- rntmp
colnames(tmp) <- rep("",length(cn))
print(tmp,quote=FALSE)
if(any(nobs>1))cat("Number of individuals:                ",nind,"\n")
cat("Total number of observations:         ",dim(z$y)[1],"\n")
if(nind>1&&any(nobs>1)){
	if(all(diff(nobs)==0))
		cat("Number of observations per individual:",nobs[1],"\n")
 	else {
		if(nind>nindmax)cat("Range of observations per individual: ",
			range(nobs),"\n")
		else cat("Number of observations per individual:\n",
			nobs,"\n")}}
av <- rg <- NULL
for(i in 1:dim(z$y)[2]){
      y <- if(is.null(z$n)||all(is.na(z$n[,i])))z$y[,i] else z$y[,i]/z$n[,i]
      av <- c(av,if((z$type[i]=="nominal"&&(is.null(z$n)||all(is.na(z$n[,i]))))
	||z$type[i]=="ordinal")NA else mean(y,na.rm=TRUE))
      rg <- c(rg,range(y,na.rm=TRUE))}
names(av) <- cn
rg <- matrix(rg,nrow=2)
dimnames(rg) <- list(c("lower","upper"),cn)
if(!all(is.na(av))){
	cat("Mean response:")
	if(dim(z$y)[2]>1){
		cat("\n")
		print(av)
		cat("\n")}
	else cat("                        ",av,"\n")}
cat("Range of responses:")
if(dim(z$y)[2]>1){
	cat("\n")
	print(rg)
	cat("\n")}
else cat("                   ",rg,"\n")
if(any(is.na(z$y)))
	cat("Number of NAs:                        ",sum(is.na(z$y)),"\n")
if(!is.null(z$wt))
	cat("Number of positive weights:           ",sum(z$wt>0),"\n")
if(!is.null(z$times)){
	cat("Mean time:                            ",mean(z$times,na.rm=TRUE),"\n")
	cat("Range of times:                       ",range(z$times,na.rm=TRUE),"\n")
	if(nind>1&&is.null(z$nest)){
		mn <- if(any(z$times<0,na.rm=TRUE))z$times[cumsum(c(1,nobs[1:(nind-1)]))]
			else 0
		cat("Mean total time:                      ",mean(z$times[cumsum(nobs)]-mn,na.rm=TRUE),"\n")
		cat("Range of total times:                 ",range(z$times[cumsum(nobs)]-mn,na.rm=TRUE),"\n")}}
if(!is.null(z$nest))
	cat("Maximum number of clusters:           ",max(z$nest),"\n")
if(!is.null(z$censor)){
	cens0 <- cens1 <- n0 <- n1 <- NULL
	for(i in 1:dim(z$y)[2]){
		if(sum(z$censor[,i]==0,na.rm=TRUE)>0){
			cens0 <- c(cens0,sum(z$censor[,i]==0,na.rm=TRUE))
			n0 <- c(n0,cn[i])}
		if(sum(z$censor[,i]==-1,na.rm=TRUE)>0){
			cens1 <- c(cens1,sum(z$censor[,i]==-1,na.rm=TRUE))
			n1 <- c(n1,cn[i])}}
	names(cens0) <- n0
	names(cens1) <- n1
	if(!is.null(cens0)){
		cat("Number of right-censored observations:")
		if(length(cens0)>1){
			cat("\n")
			print(cens0)
			cat("\n")}
		else cat(" ",cens0," (",n0,")\n",sep="")}
	if(!is.null(cens1)){
		cat("Number of left-censored observations:")
		if(length(cens1)>1){
			cat("\n")
			print(cens1)
			cat("\n")}
		else cat("  ",cens1," (",n1,")\n",sep="")}}
if(!is.null(z$delta)&&length(z$delta)==1)
	cat("Unit of measurement:                  ",z$delta,"\n")
if(!is.null(z$description))for(i in 1:length(z$description)){
	cat(names(z$description)[i],": ",sep="")
	cat(z$description[[i]],"\n")}}

print.tccov <- function(x, ...){
  z <- x; rm(x)
if(is.function(z))print.default(unclass(z))
else {
	tmp <- matrix(colnames(z$ccov),nrow=1)
	rn <- "Names:"
	if(!is.null(z$units)){
		tmp <- rbind(tmp,z$units)
		rn <- c(rn,"Units:")}
	dimnames(tmp) <- list(rn,rep("",dim(z$ccov)[2]))
	print(tmp,quote=FALSE)
	cat("Number of individuals:             ",dim(z$ccov)[1],"\n")
	if(!is.null(z$description))for(i in 1:length(z$description)){
		cat(names(z$description)[i],": ",sep="")
		cat(z$description[[i]],"\n")}}}

print.tvcov <- function(x, nindmax=50, ...){
  z <- x; rm(x)
if(is.function(z))print.default(unclass(z))
else {
	tmp <- matrix(colnames(z$tvcov),nrow=1)
	rn <- "Names:"
	if(!is.null(z$units)){
		tmp <- rbind(tmp,z$units)
		rn <- c(rn,"Units:")}
	dimnames(tmp) <- list(rn,rep("",dim(z$tvcov)[2]))
	print(tmp,quote=FALSE)
	cat("Number of individuals:               ",length(nobs(z)),"\n")
	cat("Number of observations:              ",sum(nobs(z)),"\n")
	if(length(nobs(z))>nindmax)cat("Range of observations per individual:",
		range(nobs(z)),"\n")
	else cat("Number of observations per individual:\n",
		nobs(z),"\n")
	if(!is.null(z$description))for(i in 1:length(z$description)){
		cat(names(z$description)[i],": ",sep="")
		cat(z$description[[i]],"\n")}}}

print.repeated <- function(x, nindmax=50, ...){
  z <- x; rm(x)
if(is.function(z))print.default(unclass(z))
else {
	cat("\nResponse variable:\n")
	print.response(z$response,nindmax=nindmax)
	if(!is.null(z$ccov)){
		cat("\nInter-unit (time-constant) covariates:\n")
		print.tccov(z$ccov)}
	if(!is.null(z$tvcov)){
		cat("\nIntra-unit (time-varying) covariates:\n")
		print.tvcov(z$tvcov,nindmax=nindmax)}}}

### plot methods
###
plot.response <- function(x, name=NULL, nind=NULL, nest=1, ccov=NULL,
	add=FALSE, lty=NULL, pch=NULL, main=NULL, ylim=NULL, xlim=NULL,
	xlab=NULL, ylab=NULL, ...){
if(is.null(name)){
	if(dim(x$y)[2]>1)stop("please specify which variable to plot")
	name <- colnames(x$y)}
else if(length(name)>1)stop("only one variable can be plotted")
col <- match(name,colnames(x$y))
if(is.na(col))stop(paste(name,"not found"))
if(x$type[col]=="ordinal"){
	# special case: ordinal response
	#return(plot.ordinal(z=x,ccov=ccov,main=main,xlab=xlab,ylab=ylab,
		#xlim=xlim,ylim=ylim,lty=lty,add=add,...))
  stop(paste("email Bruce to email Jim for plot.ordinal() implementation"))
  }
if(is.null(ylab))ylab <- name
if(is.null(x$times)){
#
# when no times, set up for index plot
#
	if(all(nobs(x)==1)){
		x$times <- 1:length(nobs(x))
		# set to value different from 1 so not time series
		x$nobs <- 5}
	else x$times <- sequence(nobs(x))
	if(is.null(xlab)) xlab <- "Index number"}
else if(is.null(xlab)) xlab <- "Time"
if(is.null(ylim))ylim <- range(x$y[,col],na.rm=TRUE)
if(is.null(xlim))xlim <- range(x$times,na.rm=TRUE)
tnest <- if(!is.null(x$nest)) x$nest else 1
#
# initialize
#
nm <- covind(x)
j <- 1
lt <- 0
#
# if no individuals chosen, plot them all
#
if(is.null(nind))nind <- 1:length(nobs(x))
#
# if binomial, plot proportions
#
y <- if(is.null(x$n)||all(is.na(x$n[,col])))x$y[,col] else x$y[,col]/x$n[,col]
if(!is.null(lty)){
#
# set up line types
#
	if(length(lty)==1)lty <- rep(lty,length(nind))
	else if(length(lty)!=length(nind))
		stop("lty must have one value for each item in nind")}
if(!is.null(pch)){
#
# set up symbol types
#
	if(length(pch)==1)pch <- rep(pch,length(nind))
	else if(length(pch)!=length(nind))
		stop("pch must have one value for each item in nind")}
for(i in 1:length(nobs(x)))if(any(i==nind))for(k in nest){
	lt <- if(is.null(lty))lt%%6+1 else lty[j]
	if(!add&&j==1)plot(x$times[nm==i&k==tnest],y[nm==i&k==tnest],lty=lt,
		type="l",ylim=ylim,xlim=xlim,main=main,ylab=ylab,xlab=xlab,...)
	else lines(x$times[nm==i&k==tnest],y[nm==i&k==tnest],lty=lt)
	if(!is.null(pch))points(x$times[nm==i&k==tnest],
		y[nm==i&k==tnest],pch=pch[j])
	j <- j+1}}

plot.repeated <- function(x, name=NULL, nind=NULL, nest=1, ccov=NULL,
	add=FALSE, lty=NULL, pch=NULL, main=NULL, ylim=NULL, xlim=NULL,
	xlab=NULL, ylab=NULL, ...){
if(is.null(name)){
	if(dim(x$response$y)[2]>1)stop("please specify which variable to plot")
	name <- colnames(x$response$y)}
else if(length(name)>1)stop("only one variable name can be supplied")
col <- match(name,colnames(x$response$y))
if(is.na(col)){
	col <- match(name,colnames(x$tvcov$tvcov))
	if(is.na(col))stop(paste(name,"not found"))
	variable <- "tvc"}
else variable <- "response"
#
# check individuals to plot
# if no individuals chosen, plot them all
#
uncov <- NULL
if(!is.null(nind)&&!is.null(ccov))
	stop("only one of nind and ccov can be specified")
if(is.null(nind)&&is.null(ccov))nind <- 1:length(nobs(x))
else if(!is.null(ccov)&&x$response$type[col]!="ordinal"){
	if(is.numeric(ccov)){
		if(length(ccov)!=dim(x$ccov$ccov)[2])
			stop("a covariate value must be given for each covariate")
	        tccov <- x$ccov$ccov
	        if(is.data.frame(tccov))for(i in 1:length(ccov)){
	        	if(is.factor(tccov[[i]]))
	        		tccov[[i]] <- as.numeric(tccov[[i]])}
	        tccov <- as.matrix(tccov)
		nind <- NULL
		for(i in 1:length(nobs(x)))
			if(all(ccov==tccov[i,]))nind <- c(nind,i)}
	else if(is.character(ccov)){
		if(is.null(x$ccov$ccov))stop("no covariates found")
		if(length(ccov)>1)
			stop("only one variable name can be given in ccov")
		col2 <- match(ccov,colnames(x$ccov$ccov))
		if(is.na(col2))stop(paste("covariate",ccov,"not found"))
		uncov <- unique(x$ccov$ccov[,col2])
		if(is.factor(uncov))uncov <- as.character(uncov)
		if(length(uncov)>6)
			stop(paste(ccov,"has too many distinct values to plot"))
		if(length(uncov)==1)uncov <- NULL}
	else stop("ccov must be a vector of covariate values or a covariate name")}
if(variable=="response"){
	# special case: ordinal response
	if(x$response$type[col]=="ordinal")
		#plot.ordinal(z=x,ccov=ccov,main=main,xlab=xlab,ylab=ylab,
		#	xlim=xlim,ylim=ylim,lty=lty,add=add,...)
	  stop(paste("email Bruce to email Jim for plot.ordinal() implementation"))
	else {
		if(is.null(uncov))plot.response(x$response,name=name,nind=nind,
			nest=nest,add=add,lty=lty,pch=pch,main=main,
			ylim=ylim,xlim=xlim,xlab=xlab,ylab=ylab,...)
		else {
			mfrow <- if(length(uncov)==2)c(2,1)
				else if(length(uncov)<5)c(2,2) else c(3,2)
			oldpar <- par(mfrow=mfrow,no.readonly=TRUE)
			for(i in uncov){
				nind <- NULL
				main <- paste(ccov,"=",i)
				for(j in 1:length(nobs(x)))
					if(i==x$ccov$ccov[j,col2])
					nind <- c(nind,j)
				plot.response(x$response,name=name,nind=nind,
				nest=nest,add=add,lty=lty,pch=pch,main=main,
				ylim=ylim,xlim=xlim,xlab=xlab,ylab=ylab,...)}
			par(oldpar)}}}
else if(variable=="tvc"){
	# set up covariate as a "response"
	if(is.null(ylab))ylab <- colnames(x$tvcov$tvcov)[col]
	zz <- list(times=x$response$times,y=x$tvcov$tvcov[,col,drop=FALSE],
		nobs=x$tvcov$nobs,n=NULL,type="unknown")
	class(zz) <- "response"
	if(is.null(uncov))plot.response(zz,name=name,nind=nind,nest=nest,
		add=add,lty=lty,pch=pch,main=main,ylim=ylim,xlim=xlim,
		xlab=xlab,ylab=ylab,...)
	else {
		mfrow <- if(length(uncov)==2)c(2,1)
			else if(length(uncov)<5)c(2,2) else c(3,2)
		oldpar <- par(mfrow=mfrow,no.readonly=TRUE)
		for(i in uncov){
			nind <- NULL
			main <- paste(ccov,"=",i)
			for(j in 1:length(nobs(x)))
				if(i==x$ccov$ccov[j,col2])
				nind <- c(nind,j)
			plot.response(zz,name=name,nind=nind,nest=nest,add=add,
			lty=lty,pch=pch,main=main,ylim=ylim,xlim=xlim,
			xlab=xlab,ylab=ylab,...)}
		par(oldpar)}}}

### methods to find the response variable
###
response <- function(z, ...) UseMethod("response")

response.response <- function(z, nind=NULL, names=NULL, ...){
if(is.null(nind))nind <- 1:dim(z$y)[1]
else if(length(nind)>length(nobs(z))||any(nind>length(nobs(z))))
	stop("Individual not found")
else nind <- !is.na(match(covind(z),nind))
if(all(!nind))stop("No such individuals")
if(is.null(names))col <- 1:dim(z$y)[2]
else {
	col <- match(names,colnames(z$y))
	if(any(is.na(col)))stop(paste(names[is.na(col)],"not found"))}
cn <- tmp <- NULL
for(i in col){
	if(!is.null(z$n)&&!any(is.na(z$n[,i]))){
	# binomial response
		tmp <- cbind(tmp,z$y[,i],z$n[,i]-z$y[,i])
		cn <- c(cn,colnames(z$y)[i],paste("n-",colnames(z$y)[i],sep=""))}
	else if(!is.null(z$censor)&&!any(is.na(z$censor[,i]))){
	# censored response with indicator
		tmp <- cbind(tmp,z$y[,i],z$censor[,i])
		cn <- c(cn,colnames(z$y)[i],paste(colnames(z$y)[i],".cens",sep=""))}
	else {
		tmp <- cbind(tmp,z$y[,i])
		cn <- c(cn,colnames(z$y)[i])}}
colnames(tmp) <- cn
tmp[nind,]}

response.repeated <- function(z, nind=NULL, names=NULL, ...){
if(is.null(nind))nind <- 1:dim(z$response$y)[1]
else if(length(nind)>length(nobs(z))||any(nind>length(nobs(z))))
	stop("Individual not found")
else nind <- !is.na(match(covind(z),nind))
if(all(!nind))stop("No such individuals")
if(is.null(names))col <- 1:dim(z$response$y)[2]
else {
	col <- match(names,colnames(z$response$y))
	if(any(is.na(col)))stop(paste(names[is.na(col)],"not found"))}
cn <- tmp <- NULL
for(i in col){
	if(!is.null(z$response$n)&&!any(is.na(z$response$n[,i]))){
	# binomial response
		tmp <- cbind(tmp,z$response$y[,i],z$response$n[,i]-z$response$y[,i])
		cn <- c(cn,colnames(z$response$y)[i],paste("n-",colnames(z$response$y)[i],sep=""))}
	else if(!is.null(z$response$censor)&&!any(is.na(z$response$censor[,i]))){
	# censored response with indicator
		tmp <- cbind(tmp,z$response$y[,i],z$response$censor[,i])
		cn <- c(cn,colnames(z$response$y)[i],paste(colnames(z$response$y)[i],".cens",sep=""))}
	else {
		tmp <- cbind(tmp,z$response$y[,i])
		cn <- c(cn,colnames(z$response$y)[i])}}
colnames(tmp) <- cn
tmp[nind,]}

### methods for indexing of time-constant covariates for individuals
###
covind <- function(z, ...) UseMethod("covind")

covind.default <- function(z, ...) rep(1:length(nobs(z)),nobs(z))

### methods to find numbers of observations/individual
###
nobs <- function(z, ...) UseMethod("nobs")

nobs.default <- function(z, ...) {
if(is.null(z$response)||is.null(z$response$nobs))return(NULL)
if(length(z$response$nobs)>1||z$response$nobs>1)z$response$nobs
else rep(1,dim(z$response$y)[1])}

nobs.response <- function(z, ...) {
if(length(z$nobs)>1||z$nobs>1)z$nobs
else rep(1,length(z$y))}

nobs.tvcov <- function(z, ...) z$nobs

nobs.data.frame <- function(z, ...) rep(1,dim(z)[1])

### methods to find times
###
times <- function(z, ...) UseMethod("times")

times.default <- function(z, nind=NULL, ...){
if(is.null(nind)||is.null(z$response$times))return(z$response$times)
else if(length(nind)>length(nobs(z))||any(nind>length(nobs(z))))
	stop("Individual not found")
else nind <- !is.na(match(covind(z),nind))
if(all(!nind))stop("No such individuals")
z$response$times[nind]}

times.response <- function(z, nind=NULL, ...){
if(is.null(nind)||is.null(z$times))return(z$times)
else if(length(nind)>length(nobs(z))||any(nind>length(nobs(z))))
	stop("Individual not found")
else nind <- !is.na(match(covind(z),nind))
if(all(!nind))stop("No such individuals")
z$times[nind]}

### methods to find unit of measurement/Jacobian
###
delta <- function(z, ...) UseMethod("delta")

delta.response <- function(z, nind=NULL, names=NULL, ...){
#
# find individuals
#
if(is.null(z$delta))return(NULL)
if(is.null(nind))nind <- 1:dim(z$y)[1]
else if(length(nind)>length(nobs(z))||any(nind>length(nobs(z))))
	stop("Individual not found")
else nind <- !is.na(match(covind(z),nind))
if(all(!nind))stop("No such individuals")
#
# find variables
#
col <- if(is.null(names))1:dim(z$y)[2] else match(names,colnames(z$y))
if(any(is.na(col)))stop(paste(names[is.na(col)],"not found"))
z$delta[nind,col]}

delta.repeated <- function(z, nind=NULL, names=NULL, ...){
#
# find individuals
#
if(is.null(z$response$delta))return(NULL)
if(is.null(nind))nind <- 1:dim(z$response$y)[1]
else if(length(nind)>length(nobs(z))||any(nind>length(nobs(z))))
	stop("Individual not found")
else nind <- !is.na(match(covind(z),nind))
if(all(!nind))stop("No such individuals")
#
# find variables
#
col <- if(is.null(names))1:dim(z$response$y)[2]
	else match(names,colnames(z$response$y))
print(col)
if(any(is.na(col)))stop(paste(names[is.na(col)],"not found"))
z$response$delta[nind,col]}

### methods to find weights
###
#weights <- function(object, ...) UseMethod("weights")

weights.response <- function(object, nind=NULL, ...){
if(is.null(nind)||is.null(object$wt))return(object$wt)
else if(length(nind)>length(nobs(object))||any(nind>length(nobs(object))))
	stop("Individual not found")
else nind <- !is.na(match(covind(object),nind))
if(all(!nind))stop("No such individuals")
object$wt[nind]}

weights.repeated <- function(object, nind=NULL, ...){
if(is.null(nind)||is.null(object$response$wt))return(object$response$wt)
else if(length(nind)>length(nobs(object))||any(nind>length(nobs(object))))
	stop("Individual not found")
else nind <- !is.na(match(covind(object),nind))
if(all(!nind))stop("No such individuals")
object$response$wt[nind]}

### methods to find nesting indicators
###
nesting <- function(z, ...) UseMethod("nesting")

nesting.response <- function(z, nind=NULL, ...){
if(is.null(nind))nind <- 1:length(z$y)
else if(length(nind)>length(nobs(z))||any(nind>length(nobs(z))))
	stop("Individual not found")
else nind <- !is.na(match(covind(z),nind))
if(all(!nind))stop("No such individuals")
#
# if nest is NULL, return individual index otherwise both
#
if(length(nobs(z))==1||all(nobs(z)==1))return(NULL)
else if(is.null(z$nest))return(covind(z)[nind])
else {
	z <- cbind(covind(z),z$nest)
	colnames(z) <- c("Individual","Cluster")
	return(z)[nind,,drop=FALSE]}}

nesting.repeated <- function(z, nind=NULL, ...){
if(is.null(nind))nind <- 1:dim(z$response$y)[1]
else if(length(nind)>length(nobs(z))||any(nind>length(nobs(z))))
	stop("Individual not found")
else nind <- !is.na(match(covind(z),nind))
if(all(!nind))stop("No such individuals")
#
# if nest is NULL, return individual index otherwise both
#
if(length(nobs(z))==1||all(nobs(z)==1))return(NULL)
else if(is.null(z$response$nest))return(covind(z)[nind])
else {
	z <- cbind(covind(z),z$response$nest)
	colnames(z) <- c("Individual","Cluster")
	return(z[nind,,drop=FALSE])}}

### methods to find covariates
###
covariates <- function(z, ...) UseMethod("covariates")

covariates.tccov <- function(z, nind=NULL, names=NULL, expand=FALSE, ...){
if(is.null(nind))nind <- 1:dim(z$ccov)[1]
else if(length(nind)>dim(z$ccov)[1]||any(nind>dim(z$ccov)[1])||any(nind<1))
	stop("Individual not found")
if(is.null(names))return(z$ccov[nind,])
else {
	col <- match(names,colnames(z$ccov))
	if(any(is.na(col)))
		stop(paste("covariate(s)",names[is.na(col)],"not found"))
	return(z$ccov[nind,col])}}

covariates.tvcov <- function(z, nind=NULL, names=NULL, expand=FALSE, ...){
if(is.null(nind))nind <- 1:dim(z$tvcov)[1]
else if(length(nind)>length(nobs(z))||any(nind>length(nobs(z))))
	stop("Individual not found")
else nind <- !is.na(match(covind(z),nind))
if(all(!nind))stop("No such individuals")
if(is.null(names))return(z$tvcov[nind,])
else {
	col <- match(names,colnames(z$tvcov))
	if(any(is.na(col)))
		stop(paste("covariate(s)",names[is.na(col)],"not found"))
	return(z$tvcov[nind,col])}}

covariates.repeated <- function(z, nind=NULL, names=NULL, expand=FALSE, ...){
if(expand&&!is.null(nind))stop("can only expand for all individuals")
ind <- covind(z)
if(is.null(nind)){
	nindv <- 1:dim(z$response$y)[1]
	nind <- if(expand)ind else 1:length(nobs(z))}
else if(length(nind)>length(nobs(z))||any(nind>length(nobs(z))))
	stop("Individual not found")
else nindv <- !is.na(match(ind,nind))
if(all(!nindv))stop("No such individuals")
if(is.null(names)){
	if(is.null(z$tvcov$tvcov))return(z$ccov$ccov[nind,])
	else if(is.null(z$ccov$ccov))return(z$tvcov$tvcov[nindv,])
	else {
		if(expand)return(cbind(z$ccov$ccov[nind,],
			z$tvcov$tvcov[nindv,]))
		else return(list(ccov=z$ccov$ccov[nind,],
			tvcov=z$tvcov$tvcov[nindv,]))}}
else {
	mat1 <- match(names,colnames(z$ccov$ccov))
	mat2 <- match(names,colnames(z$tvcov$tvcov))
	if(any(is.na(mat1)&is.na(mat2)))
		stop(paste("covariate(s)",names[is.na(mat1)&is.na(mat2)],"not found"))
	if(all(is.na(mat1)))return(z$tvcov$tvcov[nindv,mat2])
	else if(all(is.na(mat2)))return(z$ccov$ccov[nind,mat1])
	else {
		if(expand)return(cbind(z$ccov$ccov[nind,mat1],
			z$tvcov$tvcov[nindv,mat2]))
		else return(list(ccov=z$ccov$ccov[nind,mat1],
			tvcov=z$tvcov$tvcov[nindv,mat2]))}}}

### methods to find names
###
names.response <- function(x, ...) colnames(x$y)

names.tccov <- function(x, ...) colnames(x$ccov)

names.tvcov <- function(x, ...) colnames(x$tvcov)

names.repeated <- function(x, ...)
	list(response=colnames(x$response$y),ccov=colnames(x$ccov$ccov),
		tvcov=colnames(x$tvcov$tvcov))

### methods to find units of measurements
###
units <- function(x, ...) UseMethod("units")

units.default <- function(x, ...) x$units

units.repeated <- function(x, ...)
	list(response=units(x$response),ccov=units(x$ccov),
		tvcov=units(x$tvcov))

### methods to find description of variables
###
description <- function(z, ...) UseMethod("description")

description.default <- function(z, ...) z$description

description.repeated <- function(z, ...)
	list(response=description(z$response),ccov=description(z$ccov),
		tvcov=description(z$tvcov))

### methods to find response type(s)
###
resptype <- function(z, ...) UseMethod("resptype")

resptype.response <- function(z, ...) z$type

resptype.repeated <- function(z, ...) z$response$type

### methods to find formula used in tccov
###
formula.tccov <- function(x, ...) x$linear

formula.repeated <- function(x, ...) x$ccov$linear

### methods to transform response, times, or covariates
###
transform.response <- function(`_data`, times=NULL, units=NULL, ...){
  z <- `_data`; rm(`_data`)
if(is.call(substitute(times)))times <- substitute(times)
tran <- as.list(substitute(list(...)))[-1]
if(!is.null(tran)){
#
# transform response
#
	if(is.null(z$delta))
		z$delta <- matrix(1,nrow=dim(z$y)[1],ncol=dim(z$y)[2])
	else if(length(delta)==1)
		z$delta <- matrix(z$delta,nrow=dim(z$y)[1],ncol=dim(z$y)[2])
	cn <- colnames(z$y)
	cn2 <- names(tran)
	col <- match(cn2,cn)
	col2 <- NULL
	if(!is.null(units)){
		if(length(units)!=length(tran))
			stop(paste(length(tran),"units required"))
		if(!is.character(units))
			stop("units must be a character vector")}
	for(i in tran){
		tmp <- NULL
		for(j in 1:length(cn)){
			if(length(grep(cn[j],as.character(i)))>0){
				tmp <- j
				break}}
		if(is.null(tmp))stop("variable to transform not found")
		col2 <- c(col2,tmp)}
	j <- 0
	for(i in tran){
		j <- j+1
		if(z$type[col2[j]]!="continuous"&&z$type[col2[j]]!="duration"&&z$type[col2[j]]!="unknown")
			stop(paste("transformations do not make sense with",z$type[col2[j]],"responses"))
		# transform
		tran <- eval(deriv(i,cn[col2[j]]),as.data.frame(z$y),NULL)
		# calculate Jacobian
		jacob <- as.vector(abs(attr(tran,"gradient")))
		if(any(is.na(jacob)&!is.na(tran)))
			stop("NAs in jacobian - invalid transformation")
		if(any(abs(jacob)==Inf,na.rm=TRUE))
			stop("infinite jacobian - invalid transformation")
		if(any(jacob<=0,na.rm=TRUE))
			stop("nonpositive value in jacobian - invalid transformation")
		# store in the response object, updating delta, units, type
		if(is.na(col[j])){
			if(any(is.na(tran)&!is.na(z$y[,col2[j]]),na.rm=TRUE))
				stop("NAs created by transformation")
			tran <- as.matrix(tran)
			colnames(tran) <- cn2[j]
			z$y <- cbind(z$y,tran)
			z$delta <- if(all(is.na(z$delta[,col2[j]])))
				cbind(z$delta,jacob)
				else cbind(z$delta,z$delta[,col2[j]]*jacob)
			colnames(z$delta) <- colnames(z$y)
			if(!is.null(z$n)){
				z$n <- cbind(z$n,rep(NA,dim(z$n)[1]))
				colnames(z$n) <- colnames(z$y)}
			if(!is.null(z$censor)){
				z$censor <- cbind(z$censor,z$censor[,col2[j]])
				colnames(z$censor) <- colnames(z$y)}
			z$type <- c(z$type,z$type[col2[j]])
			names(z$type) <- colnames(z$y)
			if(!is.null(z$units)){
				z$units <- c(z$units,if(is.null(units))NA else
					units[j])
				names(z$units) <- colnames(z$y)}}
		else {
			if(any(is.na(tran)&!is.na(z$y[,col[j]]),na.rm=TRUE))
				stop("NAs created by transformation")
			z$y[,col[j]] <- as.vector(tran)
			z$delta[,col[j]] <- if(all(is.na(z$delta[,col[j]])))
				jacob else z$delta[,col[j]]*jacob
			if(!is.null(z$units))
				z$units[col[j]] <- if(is.null(units))NA
					else units[j]}}}
if(!is.null(z$units)&&all(is.na(z$units)))z$units <- NULL
if(!is.null(times)){
#
# transform times
#
	z$times <- eval(times,z,NULL)
	for(i in 1:length(nobs(z)))if(any(diff(z$times[covind(z)==i])<0))
		stop("transformation produces negative time steps")}
z}

transform.repeated <- function(`_data`, times=NULL, ...){
    z <- `_data`; rm(`_data`)
if(is.call(substitute(times)))times <- substitute(times)
z$response <- transform.response(z$response,times,...)
z}

transform.tccov <- function(`_data`, ...){
    z <- `_data`; rm(`_data`)
isf <- is.data.frame(z$ccov)
if(!isf)z$ccov <- as.data.frame(z$ccov)
#
# find transformations
#
e <- eval(substitute(list(...)),z$ccov,NULL)
tags <- names(e)
for(i in 1:length(e))if(all(is.na(e[[i]])))
	stop(paste(tags[i],"defines an invalid tranformation\n or attempts to transform a factor variable"))
#
# find covariates to transform
#
inx <- match(tags,colnames(z$ccov))
matched <- !is.na(inx)
if(any(matched))z$ccov[inx[matched]] <- e[matched]
if(!all(matched))z$ccov <- data.frame(z$ccov,e[!matched])
if(!isf)z$ccov <- as.matrix(z$ccov)
z}

transform.tvcov <- function(`_data`, ...){
    z <- `_data`; rm(`_data`)
isf <- is.data.frame(z$tvcov)
if(!isf)z$tvcov <- as.data.frame(z$tvcov)
#
# find transformations
#
e <- eval(substitute(list(...)),z$tvcov,NULL)
tags <- names(e)
for(i in 1:length(e))if(all(is.na(e[[i]])))
	stop(paste(tags[i],"defines an invalid tranformation\n or attempts to transform a factor variable"))
#
# find covariates to transform
#
inx <- match(tags,colnames(z$tvcov))
matched <- !is.na(inx)
if(any(matched))z$tvcov[inx[matched]] <- e[matched]
if(!all(matched))z$tvcov <- data.frame(z$tvcov,e[!matched])
if(!isf)z$tvcov <- as.matrix(z$tvcov)
z}

### as.data.frame methods
###
as.data.frame <- function(x, ...) UseMethod("as.data.frame")

as.data.frame.response <- function(x,row.names=NULL,optional=FALSE, ...){
	tmp <- data.frame(x$y)
	if(!is.null(x$n))for(i in 1:dim(x$y)[2])if(any(!is.na(x$n[,i])))
		tmp[[i]] <- I(cbind(x$y[,i],x$n[,i]-x$y[,i]))
	if(!is.null(x$censor))for(i in 1:dim(x$y)[2])
		if(any(!is.na(x$censor[,i])))
			tmp[[i]] <- I(cbind(x$y[,i],x$censor[,i]))
	cn <- colnames(x$y)
	if(length(x$nobs)!=1){
		cn <- c(cn,"individuals")
		tmp <- data.frame(tmp,as.factor(rep(1:length(x$nobs),x$nobs)))}
	if(!is.null(x$nest)){
		cn <- c(cn,"nesting")
		tmp <- data.frame(tmp,as.factor(x$nest))}
	if(!is.null(x$times)){
		cn <- c(cn,"times")
		tmp <- data.frame(tmp,x$times)}
	colnames(tmp) <- cn
	data.frame(tmp)}

as.data.frame.tccov <- function(x,row.names=NULL,optional=FALSE, ...)
	as.data.frame(x$ccov)

as.data.frame.tvcov <- function(x,row.names=NULL,optional=FALSE, ...)
	as.data.frame(x$tvcov)

as.data.frame.repeated <- function(x,row.names=NULL,optional=FALSE, ...){
	tmp <- data.frame(x$response$y)
	if(!is.null(x$response$n))for(i in 1:dim(x$response$y)[2])
		if(any(!is.na(x$response$n[,i])))
			tmp[[i]] <- I(cbind(x$response$y[,i],x$response$n[,i]-x$response$y[,i]))
	if(!is.null(x$response$censor))for(i in 1:dim(x$response$y)[2])
		if(any(!is.na(x$response$censor[,i])))
			tmp[[i]] <- I(cbind(x$response$y[,i],x$response$censor[,i]))
	cn <- colnames(x$response$y)
	if(!(length(x$response$nobs)==1)){
		cn <- c(cn,"individuals")
		tmp <- data.frame(tmp,as.factor(rep(1:length(x$response$nobs),
			x$response$nobs)))}
	if(!is.null(x$response$nest)){
		cn <- c(cn,"nesting")
		tmp <- data.frame(tmp,as.factor(x$response$nest))}
	if(!is.null(x$response$times)){
		cn <- c(cn,"times")
		tmp <- data.frame(tmp,x$response$times)}
	tmp <- data.frame(tmp)
	colnames(tmp) <- cn
	if(!is.null(x$ccov$ccov))
		tmp <- data.frame(tmp,x$ccov$ccov[covind(x),,drop=FALSE])
	if(!is.null(x$tvcov$tvcov))
		tmp <- data.frame(tmp,x$tvcov$tvcov)
	tmp}

### as.matrix methods
###
as.matrix <- function(x, ...) UseMethod("as.matrix")

as.matrix.response <- function(x, ...){
	tmp <- x$y
	cn <- colnames(x$y)
	if(!is.null(x$times)){
		cn <- c(cn,"times")
		tmp <- cbind(tmp,x$times)}
	colnames(tmp) <- cn
	tmp}

as.matrix.tccov <- function(x, ...) as.matrix(x$ccov)

as.matrix.tvcov <- function(x, ...) as.matrix(x$tvcov)

as.matrix.repeated <- function(x, ...){
	tmp <- x$response$y
	cn <- colnames(x$response$y)
	if(!is.null(x$response$times)){
		cn <- c(cn,"times")
		tmp <- cbind(tmp,x$response$times)}
	colnames(tmp) <- cn
	if(!is.null(x$ccov$ccov))
		tmp <- cbind(tmp,x$ccov$ccov[covind(x),,drop=FALSE])
	if(!is.null(x$tvcov$tvcov))
		tmp <- cbind(tmp,x$tvcov$tvcov)
	tmp}
swihart/rmutil documentation built on Oct. 30, 2022, 9:33 a.m.
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swihart/rmutil
Utilities for Nonlinear Regression and Repeated Measurements Models

R/objectrm.r
In swihart/rmutil: Utilities for Nonlinear Regression and Repeated Measurements Models

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swihart/rmutil Utilities for Nonlinear Regression and Repeated Measurements Models

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Utilities for Nonlinear Regression and Repeated Measurements Models

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In swihart/rmutil: Utilities for Nonlinear Regression and Repeated Measurements Models
