joineRML (version 0.4.6)

fixef.mjoint: Extract fixed effects estimates from an mjoint object

Description

Extract fixed effects estimates from an mjoint object.

Usage

# S3 method for mjoint
fixef(object, process = c("Longitudinal", "Event"), ...)

Value

A named vector of length equal to the number of sub-model coefficients estimated.

Arguments

object

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

process

character string: if process='Longitudinal' the fixed effects coefficients from the (multivariate) longitudinal sub-model are returned. Else, if process='Event', the coefficients from the time-to-event sub-model are returned.

...

additional arguments; currently none are used.

Author

Graeme L. Hickey ()

References

Pinheiro JC, Bates DM. Mixed-Effects Models in S and S-PLUS. New York: Springer Verlag; 2000.

Wulfsohn MS, Tsiatis AA. A joint model for survival and longitudinal data measured with error. Biometrics. 1997; 53(1): 330-339.

See Also

fixef for the generic method description, and ranef.mjoint.

Examples

# Fit a classical univariate joint model with a single longitudinal outcome
# and a single time-to-event outcome

data(heart.valve)
hvd <- heart.valve[!is.na(heart.valve$log.grad) & !is.na(heart.valve$log.lvmi), ]

set.seed(1)
fit1 <- mjoint(formLongFixed = log.lvmi ~ time + age,
    formLongRandom = ~ time | num,
    formSurv = Surv(fuyrs, status) ~ age,
    data = hvd,
    timeVar = "time",
    control = list(nMCscale = 2, burnin = 5)) # controls for illustration only

fixef(fit1, process = "Longitudinal")
fixef(fit1, process = "Event")

if (FALSE) {
# 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)

fixef(fit2, process = "Longitudinal")
fixef(fit2, process = "Event")
}