

   CCrreeaattee aa rreeppeeaatteedd oobbjjeecctt,, rreemmoovviinngg NNAAss

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

   AArrgguummeennttss::

   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 informa-
             tion.

   DDeessccrriippttiioonn::

        `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.

   VVaalluuee::

        Returns an object of class, repeated, containing a list
        of the response object (z$response, so that, for exam-
        ple, the response vector is z$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'.

   AAuutthhoorr((ss))::

        J.K. Lindsey

   SSeeee AAllssoo::

        `carma', `elliptic', `gettvc', `kalcount', `kalseries',
        `nbkal', `read.list', `restovec', `tcctomat', `tvc-
        tomat'.

   EExxaammpplleess::

        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)

