JM (version 0.2-1)

coef: Estimated Coefficients for Joint Models

Description

Extracts estimated coefficients from fitted joint models.

Usage

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

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 "ph-GH" or "ch-Laplace", the estimated B-spline coefficients are included as well.

...

additional arguments; currently none is used.

Value

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

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

# 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, under the additive log cumulative hazard model
fitJOINT <- jointModel(fitLME, fitCOX, 
    timeVar = "obstime", method = "ch-GH")

# 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")

# fixed effects for the event process, 
# include spline coefficients 
fixef(fitJOINT, process = "Event", include.splineCoefs = TRUE)