JM (version 1.5-2)

coef: Estimated Coefficients for Joint Models

Description

Extracts estimated coefficients from fitted joint models.

Usage

# S3 method for jointModel
coef(object, process = c("Longitudinal", "Event"), 
    include.splineCoefs = FALSE, ...)
# S3 method for jointModel
fixef(object, process = c("Longitudinal", "Event"), 
    include.splineCoefs = FALSE, ...)

Value

A numeric vector or a matrix of the estimated parameters for the fitted model.

Arguments

object

an object inheriting from class jointModel.

process

for which model (i.e., linear mixed model or survival model) to extract the estimated coefficients.

include.splineCoefs

logical; if TRUE and the method argument in jointModel() is "ch-Laplace", the estimated B-spline coefficients are included as well.

...

additional arguments; currently none is used.

Author

Dimitris Rizopoulos

Details

When process = "Event" both methods return the same output. However, for process = "Longitudinal", the coef() method returns the subject-specific coefficients, whereas fixef() only the fixed effects.

See Also

ranef.jointModel

Examples

if (FALSE) {
# linear mixed model fit
fitLME <- lme(sqrt(CD4) ~ obstime * drug - drug, 
    random = ~ 1 | patient, data = aids)
# cox model fit
fitCOX <- coxph(Surv(Time, death) ~ drug, data = aids.id, x = TRUE)

# joint model fit
fitJOINT <- jointModel(fitLME, fitCOX, 
    timeVar = "obstime")

# fixed effects for the longitudinal process
fixef(fitJOINT)

# fixed effects + random effects estimates for the longitudinal 
# process
coef(fitJOINT)

# fixed effects for the event process
fixef(fitJOINT, process = "Event")
coef(fitJOINT, process = "Event")
}