R: Create a repeated Object, Removing NAs

rmna {rmutil} | R Documentation

## 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)

[Package rmutil version 1.1.3 Index]