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logLik.mjoint

Extract log-likelihood from an mjoint object


Description

Extract log-likelihood from an mjoint object.

Usage

## S3 method for class 'mjoint'
logLik(object, ...)

Arguments

object

an object inheriting from class mjoint for a joint model of time-to-event and multivariate longitudinal data.

...

additional arguments; currently none are used.

Value

Returns an object of class logLik. This is a number with two attributes: df (degrees of freedom), giving the number of parameters in the model, and nobs, the number of observations used in estimation.

Author(s)

Graeme L. Hickey (graemeleehickey@gmail.com)

References

Henderson R, Diggle PJ, Dobson A. Joint modelling of longitudinal measurements and event time data. Biostatistics. 2000; 1(4): 465-480.

See Also

logLik for the generic method description.

Examples

## Not run: 
# Fit a joint model with bivariate longitudinal outcomes

data(heart.valve)
hvd <- heart.valve[!is.na(heart.valve$log.grad) & !is.na(heart.valve$log.lvmi), ]
fit2 <- mjoint(
    formLongFixed = list("grad" = log.grad ~ time + sex + hs,
                         "lvmi" = log.lvmi ~ time + sex),
    formLongRandom = list("grad" = ~ 1 | num,
                          "lvmi" = ~ time | num),
    formSurv = Surv(fuyrs, status) ~ age,
    data = list(hvd, hvd),
    inits = list("gamma" = c(0.11, 1.51, 0.80)),
    timeVar = "time",
    verbose = TRUE)

logLik(fit2)

## End(Not run)

joineRML

Joint Modelling of Multivariate Longitudinal Data and Time-to-Event Outcomes

v0.4.5
GPL-3 | file LICENSE
Authors
Graeme L. Hickey [cre, aut] (<https://orcid.org/0000-0002-4989-0054>), Pete Philipson [aut] (<https://orcid.org/0000-0001-7846-0208>), Andrea Jorgensen [ctb] (<https://orcid.org/0000-0002-6977-9337>), Ruwanthi Kolamunnage-Dona [aut] (<https://orcid.org/0000-0003-3886-6208>), Paula Williamson [ctb] (<https://orcid.org/0000-0001-9802-6636>), Dimitris Rizopoulos [ctb, dtc] (data/renal.rda, R/hessian.R, R/vcov.R), Alessandro Gasparini [aut] (<https://orcid.org/0000-0002-8319-7624>), Medical Research Council [fnd] (Grant number: MR/M013227/1)
Initial release
2021-04-21

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