  In survival studies it is important to record the values of key longitudinal
covariates until the occurrence of event of a subject. For this reason, it is
essential to study the association between longitudinal and time-to-event
outcomes using the joint model. In this paper, profile likelihood approach has
been used to estimate the cumulative hazard and regression parameters from the
joint model of survival and longitudinal data. Moreover, we show the asymptotic
normality of the profile likelihood estimator via asymptotic expansion of the
profile likelihood and obtain the explicit form of the variance estimator. The
estimators of the regression parameters from the joint model are shown to be
semi-parametric efficient.
