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$. Lmsurv, vector(c(Xlong.s %*% betas) + rowSums(Z.s * b))

. Xlong_deriv, s <-model.matrix( ~ X, Data.s)

. Zderiv, s <-model.matrix( ~ 1, Data.s)

$. Lmsurv, vector(c(Xlong_deriv.s %*% betas[c(2, 4)]) + rowSums(Zderiv.s * b

$. Lmsurv and <. Deathac, Death h1$cause <-1 h2 <-bh2 names(h2)

<. Haz, h1, h2) CI <-CumInc(Haz) idx <-sum(CI$time <= tpred) return(CI

#. Parametric-boostrap-av-<-lmefit, $. Apvar-pars, and <. , Pars") varFix <-lmeFit$varFix nbetas <-length(betas) nP <-length(Pars) mat <-matrix(0, nbetas + nP, nbetas + nP) mat[seq_len(nbetas), seq_len(nbetas)] <-varFix mat[nbetas + seq_len(nP), nbetas + seq_len(nP)] <-aV coef_coxFit1.MC <-mvrnorm(M, mu = coxFit1$coef, Sigma = coxFit1$var) coef_coxFit2.MC <-mvrnorm(M, mu = coxFit2$coef, Sigma = coxFit2$var) coef_long.MC <-mvrnorm(M, c(betas, Pars), Sigma = mat) for(l in seq_len(M)){ betas

. Lmsurv and . Mc-$-slope, MC <-as.vector(c(Xlong_deriv.s %*% betas.MC[c(2, 4)]) + rowSums(Zderiv.s * b

. Xsurv and . Mc, matrix( ~ 0 + X + level + slope

. Lmsurv_pred, . Mc-$-slope_pred, and . Mc, vector(c(Xlong_deriv_pred.s %*% betas.MC[c(2, 4)]) + rowSums(Zderiv_pred.s * b_pred

. Xsurv_pred and . Mc, matrix( ~ 0 + X + level + slope

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