rmna: Create a repeated Object, Removing NAs

In rmutil: Utilities for Nonlinear Regression and Repeated Measurements Models

Create a repeated Object, Removing NAs

Description

rmna forms an object of class, repeated, from a response object and possibly time-varying or intra-individual covariate (tvcov), and time-constant or inter-individual covariate (tccov) objects, removing any observations where response and covariate values have NAs. Subjects must be in the same order in all (three) objects to be combined.

Such objects can be printed and plotted. Methods are available for extracting the response, the numbers of observations per individual, the times, the weights, the units of measurement/Jacobian, the nesting variable, the covariates, and their names: response, nobs, times, weights, delta, nesting, covariates, and names.

Usage

rmna(response, ccov=NULL, tvcov=NULL)

Arguments

response	An object of class, response (created by restovec), containing the response variable information.
ccov	An object of class, tccov (created by tcctomat), containing the time-constant or inter-individual covariate information.
tvcov	An object of class, tvcov (created by tvctomat), containing the time-varying or intra-individual covariate information.

Value

Returns an object of class, repeated, containing a list of the response object (z$response, so that, for example, the response vector is z$response$y; see restovec), and possibly the two classes of covariate objects (z$ccov and z$tvcov; see tcctomat and tvctomat).

Author(s)

J.K. Lindsey

See Also

DataMethods, covariates, covind, delta, dftorep, lvna, names, nesting, nobs, read.list, read.surv, response, resptype, restovec, tcctomat, times, transform, tvctomat, units, weights

Examples

y <- matrix(rnorm(20),ncol=5)
tt <- c(1,3,6,10,15)
print(resp <- restovec(y,times=tt))
x <- c(0,0,1,1)
tcc <- tcctomat(x)
z <- matrix(rpois(20,5),ncol=5)
tvc <- tvctomat(z)
print(reps <- rmna(resp, tvcov=tvc, ccov=tcc))
response(reps)
response(reps, nind=2:3)
times(reps)
nobs(reps)
weights(reps)
covariates(reps)
covariates(reps,names="x")
covariates(reps,names="z")
names(reps)
nesting(reps)
# because individuals are the only nesting, this is the same as
covind(reps)
#
# use in glm
rm(y,x,z)
glm(y~x+z,data=as.data.frame(reps))
#
# binomial
y <- matrix(rpois(20,5),ncol=5)
print(respb <- restovec(y,totals=y+matrix(rpois(20,5),ncol=5),times=tt))
print(repsb <- rmna(respb, tvcov=tvc, ccov=tcc))
response(repsb)
#
# censored data
y <- matrix(rweibull(20,2,5),ncol=5)
print(respc <- restovec(y,censor=matrix(rbinom(20,1,0.9),ncol=5),times=tt))
print(repsc <- rmna(respc, tvcov=tvc, ccov=tcc))
# if there is no censoring, censor indicator is not printed
response(repsc)
#
# nesting clustered within individuals
nest <- c(1,1,2,2,2)
print(respn <- restovec(y,censor=matrix(rbinom(20,1,0.9),ncol=5),
	times=tt,nest=nest))
print(repsn <- rmna(respn, tvcov=tvc, ccov=tcc))
response(respn)
times(respn)
nesting(respn)

rmutil documentation built on Oct. 29, 2022, 1:08 a.m.