| rmna {rmutil} | R Documentation |
rmna forms an object of class, repeated, from a response object
and possibly time-varying covariate (tvcov), and time-constant
covariate (tccov) objects, removing any response and covariate values
that have NAs.
Such objects can be printed and plotted.
rmna(response, tvcov=NULL, ccov=NULL)
response |
An object of class, response (created by
restovec), containing the response variable information. |
tvcov |
An object of class, tvcov (created by tvctomat),
containing the time-varying covariate information. |
tccov |
An object of class, tccov (created by tcctomat),
containing the time-constant covariate information. |
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).
Methods are available for extracting the response, the numbers of
observations per individual, the times, the weights, the nesting
variable, and the covariates or their names: response,
nobs, times, weights, nesting,
covariates, and names.
J.K. Lindsey
carma, elliptic, gettvc,
kalcount, kalseries, nbkal,
read.list, restovec, tcctomat,
tvctomat.
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)
# 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)