lvna {rmutil} | R Documentation |

`lvna`

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. If there are NAs in any variables, it also
creates a logical vector indicating which observations have NAs either
in the response or the covariate values. 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`

.

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

`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. |

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`

), possibly the two
classes of covariate objects (`z$ccov`

and `z$tvcov`

; see
`tcctomat`

and `tvctomat`

),
and a logical vector (`z$NAs`

) indicating which observations have
an NA in the response or some covariate.

J.K. Lindsey

`DataMethods`

, `covariates`

,
`covind`

, `delta`

,
`dftorep`

, `names`

,
`nesting`

, `nobs`

,
`read.list`

, `read.surv`

,
`response`

, `resptype`

,
`restovec`

, `rmna`

,
`tcctomat`

, `times`

,
`transform`

, `tvctomat`

,
`units`

, `weights`

y <- matrix(rnorm(20),ncol=5) y[2,3] <- NA 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 <- lvna(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) y[2,3] <- NA print(respb <- restovec(y,totals=y+matrix(rpois(20,5),ncol=5),times=tt)) print(repsb <- lvna(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 <- lvna(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 <- lvna(respn, tvcov=tvc, ccov=tcc)) response(respn) times(respn) nesting(respn)

[Package *rmutil* version 1.0 Index]