coef {JM} | R Documentation |
Extracts estimated coefficients from fitted joint models.
## 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, ...)
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. |
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.
A numeric vector or a matrix of the estimated parameters for the fitted model.
Dimitris Rizopoulos d.rizopoulos@erasmusmc.nl
# 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)