coef function

Estimated Coefficients and Confidence Intervals for Joint Models

Extracts estimated coefficients and confidence intervals from fitted joint models.

## S3 method for class 'JMbayes'
coef(object, process = c("Longitudinal", "Event"), ...)

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

## S3 method for class 'JMbayes'
confint(object, parm = c("all", "Longitudinal", "Event"), ...)

Arguments

• object: an object inheriting from class JMbayes.
• process: for which submodel (i.e., linear mixed model or survival model) to extract the estimated coefficients.
• parm: for which submodel (i.e., linear mixed model or survival model) to extract credible intervals.
• ...: 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.

Returns

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

Author(s)

Dimitris Rizopoulos d.rizopoulos@erasmusmc.nl

See Also

ranef.JMbayes, jointModelBayes

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 <- jointModelBayes(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)