coef: Estimated Coefficients for Joint Models

In JM: Joint Modeling of Longitudinal and Survival Data

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 "ch-Laplace", the estimated B-spline coefficients are included as well.
...	additional arguments; currently none is used.

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.

Value

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

Author(s)

Dimitris Rizopoulos [e-mail]

See Also

ranef.jointModel

Examples

## Not run: 
# 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")

## End(Not run)

JM documentation built on Aug. 8, 2022, 5:09 p.m.