Nothing
R/summary.lsjm.R
In FlexVarJM: Estimate Joint Models with Subject-Specific Variance
Defines functions
summary.lsjm
#' @export
summary.lsjm <- function(object,...)
{
x <- object
if(!inherits(x, "lsjm")) stop("use only \"lsjm\" objects")
cat("Joint model for quantitative outcome and competing risks", "\n")
cat("with heterogenous variability and fitted by maximum likelihood method", "\n")
#ajouter le code d'appelle à la fonction
cat("\n")
cat("Statistical Model:", "\n")
cat(paste(" Number of subjects:", x$control$Ind),"\n")
cat(paste(" Number of observations:", nrow(x$control$data.long)),"\n")
#cat(paste(" Number of events 1:", ),"\n")
#cat(paste(" Number of events 2:", ),"\n")
cat("\n")
cat("Iteration process:", "\n")
if(x$control$conv==1) cat(" Convergence criteria satisfied")
if(x$control$conv==2) cat(" Maximum number of iteration reached without convergence")
if(x$control$conv==4) {cat(" The program stopped abnormally. No results can be displayed. \n")
}
else{
cat("\n")
cat(paste(" Number of iterations: ",x$control$niter), "\n")
cat(paste(" Convergence criteria: parameters =" ,signif(x$control$convcrit[1],3)), "\n")
cat(paste(" : likelihood =" ,signif(x$control$convcrit[2],3)), "\n")
cat(paste(" : second derivatives =" ,signif(x$control$convcrit[3],3)), "\n")
cat(paste(" Time of computation :" ,format(x$time.compute)))
}
cat("\n")
cat("\n")
cat("Goodness-of-fit statistics:")
cat("\n")
cat(paste(" Likelihood: ", x$control$likelihood_value),"\n")
cat(paste(" AIC: ", 2*nrow(x$table.res) - 2* x$control$likelihood_value),"\n")
cat("\n")
cat("Maximum Likelihood Estimates:")
#Manage parameters
curseur <- 1
param <- x$table.res$Estimation
param.se <- x$table.res$SE
param.names <- rownames(x$table.res)
#browser()
#Evenement 1 :
## Risque de base :
if(x$control$hazard_baseline == "Weibull"){
#if(scaleWeibull == "square"){
# alpha_weib <- param[curseur]**2
# curseur <- curseur + 1
# shape <- param[curseur]**2
# curseur <- curseur + 1
#}
#else{
# alpha_weib <- exp(param[curseur])
# curseur <- curseur + 1
# shape <- exp(param[curseur])
# curseur <- curseur + 1
#}
shape <- param[curseur]
shape.se <- param.se[curseur]
shape.name <- param.names[curseur]
curseur <- curseur + 1
}
if(x$control$hazard_baseline == "Splines"){
gamma <- param[(curseur):(curseur+x$control$ord.splines+1)]
gamma.se <- param.se[(curseur):(curseur+x$control$ord.splines+1)]
gamma.name <- param.names[(curseur):(curseur+x$control$ord.splines+1)]
curseur <- curseur + x$control$ord.splines + 2
}
## Covariables :
if(x$control$nb.alpha >=1){
alpha <- param[(curseur):(curseur+x$control$nb.alpha-1)]
alpha.se <- param.se[(curseur):(curseur+x$control$nb.alpha-1)]
alpha.name <- param.names[(curseur):(curseur+x$control$nb.alpha-1)]
curseur <- curseur+x$control$nb.alpha
}
## Association :
if(c("random effect") %in% x$control$sharedtype ){
stop("Not implemented yet")
}
if(c("current value") %in% x$control$sharedtype){
alpha.current <- param[curseur]
alpha.current.se <- param.se[curseur]
alpha.current.name <- param.names[curseur]
curseur <- curseur + 1
}
if(c("slope") %in% x$control$sharedtype){
alpha.slope <- param[curseur]
alpha.slope.se <- param.se[curseur]
alpha.slope.name <- param.names[curseur]
curseur <- curseur + 1
}
if(c("variability") %in% x$control$sharedtype){
alpha.sigma <- param[curseur]
alpha.sigma.se <- param.se[curseur]
alpha.sigma.name <- param.names[curseur]
curseur <- curseur + 1
}
# Evenement 2
if(x$control$competing_risk){
## Risque de base :
if(x$control$hazard_baseline_CR == "Weibull"){
#if(scaleWeibull == "square"){
# alpha_weib.CR <- param[curseur]**2
# curseur <- curseur + 1
# shape.CR <- param[curseur]**2
# curseur <- curseur + 1
#}
#else{
# alpha_weib.CR <- exp(param[curseur])
# curseur <- curseur + 1
# shape.CR <- exp(param[curseur])
# curseur <- curseur + 1
#}
shape.CR <- param[curseur]
shape.CR.se <- param.se[curseur]
shape.CR.name <- param.names[curseur]
curseur <- curseur + 1
}
if(x$control$hazard_baseline_CR == "Splines"){
gamma.CR <- param[(curseur):(curseur+x$control$ord.splines+1)]
gamma.CR.se <- param.se[(curseur):(curseur+x$control$ord.splines+1)]
gamma.CR.name <- param.names[(curseur):(curseur+x$control$ord.splines+1)]
curseur <- curseur + x$control$ord.splines + 2
}
## Covariables :
if(x$control$nb.alpha.CR >=1){
alpha.CR <- param[(curseur):(curseur+x$control$nb.alpha.CR-1)]
alpha.CR.se <- param.se[(curseur):(curseur+x$control$nb.alpha.CR-1)]
alpha.CR.name <- param.names[(curseur):(curseur+x$control$nb.alpha.CR-1)]
curseur <- curseur+x$control$nb.alpha.CR
}
## Association :
if(c("random effect") %in% x$control$sharedtype_CR){
stop("Not implemented yet")
}
if(c("current value") %in% x$control$sharedtype_CR){
alpha.current.CR <- param[curseur]
alpha.current.CR.se <- param.se[curseur]
alpha.current.CR.name <- param.names[curseur]
curseur <- curseur + 1
}
if(c("slope") %in% x$control$sharedtype_CR){
alpha.slope.CR <- param[curseur]
alpha.slope.CR.se <- param.se[curseur]
alpha.slope.CR.name <- param.names[curseur]
curseur <- curseur + 1
}
if(c("variability") %in% x$control$sharedtype_CR){
alpha.sigma.CR <- param[curseur]
alpha.sigma.CR.se <- param.se[curseur]
alpha.sigma.CR.name <- param.names[curseur]
curseur <- curseur + 1
}
}
# Marqueur :
## Effets fixes trend :
beta <- param[curseur:(curseur+x$control$nb.priorMean.beta-1)]
beta.se <- param.se[curseur:(curseur+x$control$nb.priorMean.beta-1)]
beta.name <- param.names[curseur:(curseur+x$control$nb.priorMean.beta-1)]
curseur <- curseur+x$control$nb.priorMean.beta
## Effets fixes var :
if(x$control$variability_hetero){
omega <- param[curseur:(curseur+x$control$nb.omega-1)]
omega.se <- param.se[curseur:(curseur+x$control$nb.omega-1)]
omega.name <- param.names[curseur:(curseur+x$control$nb.omega-1)]
curseur <- curseur + x$control$nb.omega
}
else{
sigma.epsilon <- param[curseur]
sigma.epsilon.se <- param.se[curseur]
sigma.epsilon.name <- param.names[curseur]
curseur <- curseur + 1
}
## Matrice de variance-covariance de l'ensemble des effets aléatoires :
if(x$control$variability_hetero){
if(x$control$correlated_re){
borne1 <- curseur + choose(n = x$control$nb.e.a, k = 2) + x$control$nb.e.a - 1
C1 <- matrix(rep(0,(x$control$nb.e.a)**2),nrow=x$control$nb.e.a,ncol=x$control$nb.e.a)
C1[lower.tri(C1, diag=T)] <- param[curseur:borne1]
C2 <- matrix(param[(borne1+1):(borne1+x$control$nb.e.a.sigma*x$control$nb.e.a)],nrow=x$control$nb.e.a.sigma,ncol=x$control$nb.e.a, byrow = TRUE)
borne2 <- borne1+x$control$nb.e.a.sigma*x$control$nb.e.a + 1
borne3 <- borne2 + choose(n = x$control$nb.e.a.sigma, k = 2) + x$control$nb.e.a.sigma - 1
C3 <- matrix(rep(0,(x$control$nb.e.a.sigma)**2),nrow=x$control$nb.e.a.sigma,ncol=x$control$nb.e.a.sigma)
C3[lower.tri(C3, diag=T)] <- param[borne2:borne3]
C4 <- matrix(rep(0,x$control$nb.e.a*x$control$nb.e.a.sigma),nrow=x$control$nb.e.a,ncol=x$control$nb.e.a.sigma)
MatCov <- rbind(cbind(C1,C4),cbind(C2,C3))
MatCov <- as.matrix(MatCov)
}
else{
borne1 <- curseur + choose(n = x$control$nb.e.a, k = 2) + x$control$nb.e.a - 1
C1 <- matrix(rep(0,(x$control$nb.e.a)**2),nrow=x$control$nb.e.a,ncol=x$control$nb.e.a)
C1[lower.tri(C1, diag=T)] <- param[curseur:borne1]
borne3 <- borne1 + choose(n = x$control$nb.e.a.sigma, k = 2) + x$control$nb.e.a.sigma
C3 <- matrix(rep(0,(x$control$nb.e.a.sigma)**2),nrow=x$control$nb.e.a.sigma,ncol=x$control$nb.e.a.sigma)
C3[lower.tri(C3, diag=T)] <- param[(borne1+1):borne3]
C4 <- matrix(rep(0,x$control$nb.e.a*x$control$nb.e.a.sigma),nrow=x$control$nb.e.a,ncol=x$control$nb.e.a.sigma)
C2.bis <- matrix(rep(0,x$control$nb.e.a*x$control$nb.e.a.sigma),nrow=x$control$nb.e.a.sigma,ncol=x$control$nb.e.a)
MatCov <- rbind(cbind(C1,C4),cbind(C2.bis,C3))
MatCov <- as.matrix(MatCov)
}
}
else{
borne1 <- curseur + choose(n = x$control$nb.e.a, k = 2) + x$control$nb.e.a - 1
C1 <- matrix(rep(0,(x$control$nb.e.a)**2),nrow=x$control$nb.e.a,ncol=x$control$nb.e.a)
C1[lower.tri(C1, diag=T)] <- param[curseur:borne1]
MatCov <- C1
}
cat("\n")
cat("Longitudinal model:")
cat("\n")
cat(" Fixed effects:")
# betas_tab <- x$table.res[grep("^beta", rownames(x$table.res)),]
#print(rownames(betas_tab))
#r.name.betas <- strsplit(rownames(betas_tab), "#§#_")
#r.name.betas2 <- c()
#for(l in r.name.betas){
# r.name.betas2 <- c(r.name.betas2, l[-1])
#}
#print(r.name.betas2)
betas_tab <- matrix(nrow = length(beta), ncol = 4)
betas_tab[,1] <- beta
betas_tab[,2] <- beta.se
betas_tab[,3] <- betas_tab[,1]/betas_tab[,2]
betas_tab[,4] <- 1 - pchisq(betas_tab[,3]**2,1)
betas_tab <- as.data.frame(betas_tab)
rownames(betas_tab) <- beta.name
colnames(betas_tab) <- c("Coeff", "SE", "Wald", "P-value")
cat("\n")
print(betas_tab)
if(x$control$variability_hetero){
cat("\n")
cat(" Fixed effects of the linear predictor associated with variability:")
var_tab <- matrix(nrow = length(omega), ncol = 4)
var_tab[,1] <- omega
var_tab[,2] <- omega.se
var_tab[,3] <- var_tab[,1]/var_tab[,2]
var_tab[,4] <- 1 - pchisq(var_tab[,3]**2,1)
var_tab <- as.data.frame(var_tab)
rownames(var_tab) <- omega.name
colnames(var_tab) <- c("Coeff", "SE", "Wald", "P-value")
cat("\n")
print(var_tab)
}
else{
cat("\n")
var_tab <- matrix(nrow = length(sigma.epsilon), ncol = 4)
var_tab[,1] <- sigma.epsilon
var_tab[,2] <- sigma.epsilon.se
var_tab[,3] <- var_tab[,1]/var_tab[,2]
var_tab[,4] <- 1 - pchisq(var_tab[,3]**2,1)
var_tab <- as.data.frame(var_tab)
rownames(var_tab) <- sigma.epsilon.name
colnames(var_tab) <- c("Coeff", "SE", "Wald", "P-value")
cat("\n")
print(var_tab)
}
cat("\n")
cat(" Covariance matrix of the random effects:")
cat("\n")
#chol_mat <- x$table.res$Estimation[grep("^chol", rownames(x$table.res))]
#chol_mat2 <- matrix(0,nrow = quad(1,1,-2*length(chol_mat)), ncol = quad(1,1,-2*length(chol_mat)) )
#chol_mat2[lower.tri(chol_mat2, diag=T)] <- chol_mat
#print(chol_mat2,quote=FALSE,na.print="")
print(MatCov%*%t(MatCov),quote=FALSE,na.print="")
cat("\n")
cat("Survival model(s):")
cat("\n")
cat(" First event:")
#browser()
e1_var_tab <- NULL
e1_share_current_tab <- NULL
e1_share_slope_tab <- NULL
e1_alpha_tab <- NULL
e1_names_tab <- c()
#browser()
if(c("variability") %in% x$control$sharedtype){
e1_var_tab <- matrix(nrow = 1, ncol = 4)
e1_var_tab[,1] <- alpha.sigma
e1_var_tab[,2] <- alpha.sigma.se
e1_var_tab[,3] <- e1_var_tab[,1]/e1_var_tab[,2]
e1_var_tab[,4] <- 1 - pchisq(e1_var_tab[,3]**2,1)
e1_names_tab <- c(e1_names_tab, alpha.sigma.name)
}
if(c("random effect") %in% x$control$sharedtype){
print("Not implemented yet")
}
if(c("current value") %in% x$control$sharedtype){
e1_share_current_tab <- matrix(nrow = 1, ncol = 4)
e1_share_current_tab[,1] <- alpha.current
e1_share_current_tab[,2] <- alpha.current.se
e1_share_current_tab[,3] <- e1_share_current_tab[,1]/e1_share_current_tab[,2]
e1_share_current_tab[,4] <- 1 - pchisq(e1_share_current_tab[,3]**2,1)
e1_names_tab <- c(e1_names_tab, alpha.current.name)
}
#leonie la plus belle <3 <3 <3
if(c("slope") %in% x$control$sharedtype){
e1_share_slope_tab <- matrix(nrow = 1, ncol = 4)
e1_share_slope_tab[,1] <- c(alpha.slope)
e1_share_slope_tab[,2] <- c(alpha.slope.se)
e1_share_slope_tab[,3] <- e1_share_slope_tab[,1]/e1_share_slope_tab[,2]
e1_share_slope_tab[,4] <- 1 - pchisq(e1_share_slope_tab[,3]**2,1)
e1_names_tab <- c(e1_names_tab, alpha.slope.name)
}
if(x$control$hazard_baseline == "Splines"){
if(x$control$nb.alpha >=1){
e1_alpha_tab <- matrix(nrow = length(alpha), ncol = 4)
e1_alpha_tab[,1] <- alpha
e1_alpha_tab[,2] <- alpha.se
e1_alpha_tab[,3] <- e1_alpha_tab[,1]/e1_alpha_tab[,2]
e1_alpha_tab[,4] <- 1 - pchisq(e1_alpha_tab[,3]**2,1)
e1_names_tab <- c(e1_names_tab, alpha.name)
}
}
else{
if(x$control$nb.alpha >=2){
e1_alpha_tab <- matrix(nrow = length(alpha)-1, ncol = 4)
e1_alpha_tab[,1] <- alpha[-1]
e1_alpha_tab[,2] <- alpha.se[-1]
e1_alpha_tab[,3] <- e1_alpha_tab[,1]/e1_alpha_tab[,2]
e1_alpha_tab[,4] <- 1 - pchisq(e1_alpha_tab[,3]**2,1)
e1_names_tab <- c(e1_names_tab, alpha.name[-1])
}
}
e1_bas_tab <- NULL
if(x$control$hazard_baseline == "Exponential"){
e1_bas_tab <- matrix(nrow = 1, ncol = 4)
e1_bas_tab[1,1] <- alpha[1]
e1_bas_tab[1,2] <- alpha.se[1]
e1_bas_tab[1,3] <- e1_bas_tab[,1]/e1_bas_tab[,2]
e1_bas_tab[1,4] <- 1 - pchisq(e1_bas_tab[,3]**2,1)
#e1_alpha_tab <- e1_alpha_tab[-1,]
e1_names_tab <- c(e1_names_tab, alpha.name[-1])
rownames(e1_bas_tab) <- c("intercept")
colnames(e1_bas_tab) <- c("Coeff", "SE", "Wald", "P-value")
}
if(x$control$hazard_baseline == "Weibull"){
e1_bas_tab <- matrix(nrow = 2, ncol = 4)
e1_bas_tab[1,1] <- alpha[1]
e1_bas_tab[1,2] <- alpha.se[1]
#e1_bas_tab[1,] <- e1_alpha_tab[1,]
#e1_alpha_tab <- e1_alpha_tab[-1,]
#e1_names_tab <- c(e1_names_tab, alpha.name[-1])
e1_bas_tab[2,1] <- shape
e1_bas_tab[2,2] <- shape.se
e1_bas_tab[,3] <- e1_bas_tab[,1]/e1_bas_tab[,2]
e1_bas_tab[,4] <- 1 - pchisq(e1_bas_tab[,3]**2,1)
rownames(e1_bas_tab) <- c("intercept",shape.name)
colnames(e1_bas_tab) <- c("Coeff", "SE", "Wald", "P-value")
}
if(x$control$hazard_baseline == "Splines"){
e1_bas_tab <- matrix(nrow = length(gamma), ncol = 4)
e1_bas_tab[,1] <- gamma
e1_bas_tab[,2] <- gamma.se
e1_bas_tab[,3] <- e1_bas_tab[,1]/e1_bas_tab[,2]
e1_bas_tab[,4] <- 1 - pchisq(e1_bas_tab[,3]**2,1)
rownames(e1_bas_tab) <- gamma.name
colnames(e1_bas_tab) <- c("Coeff", "SE", "Wald", "P-value")
}
e1_surv_tab <- rbind(e1_var_tab, e1_share_current_tab, e1_share_slope_tab, e1_alpha_tab)
rownames(e1_surv_tab) <- e1_names_tab
colnames(e1_surv_tab) <- c("Coeff", "SE", "Wald", "P-value")
if(nrow(e1_bas_tab)!=0){
cat("\n")
cat(" Regression:")
cat("\n")
print(e1_surv_tab)
}
cat("\n")
cat(paste(" Baseline: ",x$control$hazard_baseline), "\n")
cat("\n")
print(e1_bas_tab)
cat("\n")
if(x$control$competing_risk){
cat(" Second event:")
e2_var_tab <- NULL
e2_share_current_tab <- NULL
e2_share_slope_tab <- NULL
e2_alpha_tab <- NULL
e2_names_tab <- c()
if(c("variability") %in% x$control$sharedtype_CR){
e2_var_tab <- matrix(nrow = 1, ncol = 4)
e2_var_tab[,1] <- alpha.sigma.CR
e2_var_tab[,2] <- alpha.sigma.CR.se
e2_var_tab[,3] <- e2_var_tab[,1]/e2_var_tab[,2]
e2_var_tab[,4] <- 1 - pchisq(e2_var_tab[,3]**2,1)
e2_names_tab <- c(e2_names_tab, alpha.sigma.CR.name)
}
if(c("random effect") %in% x$control$sharedtype_CR){
print("Not implemented yet")
}
if(c("current value") %in% x$control$sharedtype_CR){
e2_share_current_tab <- matrix(nrow = 1, ncol = 4)
e2_share_current_tab[,1] <- alpha.current.CR
e2_share_current_tab[,2] <- alpha.current.CR.se
e2_share_current_tab[,3] <- e2_share_current_tab[,1]/e2_share_current_tab[,2]
e2_share_current_tab[,4] <- 1 - pchisq(e2_share_current_tab[,3]**2,1)
e2_names_tab <- c(e2_names_tab, alpha.current.CR.name)
}
if(c("slope") %in% x$control$sharedtype_CR){
e2_share_slope_tab <- matrix(nrow = 1, ncol = 4)
e2_share_slope_tab[,1] <- alpha.slope.CR
e2_share_slope_tab[,2] <- alpha.slope.CR.se
e2_share_slope_tab[,3] <- e2_share_slope_tab[,1]/e2_share_slope_tab[,2]
e2_share_slope_tab[,4] <- 1 - pchisq(e2_share_slope_tab[,3]**2,1)
e2_names_tab <- c(e2_names_tab, alpha.slope.CR.name)
}
if(x$control$hazard_baseline_CR == "Splines"){
if(x$control$nb.alpha.CR >=1){
e2_alpha_tab <- matrix(nrow = length(alpha.CR), ncol = 4)
e2_alpha_tab[,1] <- alpha.CR
e2_alpha_tab[,2] <- alpha.CR.se
e2_alpha_tab[,3] <- e2_alpha_tab[,1]/e2_alpha_tab[,2]
e2_alpha_tab[,4] <- 1 - pchisq(e2_alpha_tab[,3]**2,1)
}
}
else{
if(x$control$nb.alpha.CR >=2){
e2_alpha_tab <- matrix(nrow = length(alpha.CR)-1, ncol = 4)
e2_alpha_tab[,1] <- alpha.CR[-1]
e2_alpha_tab[,2] <- alpha.CR.se[-1]
e2_alpha_tab[,3] <- e2_alpha_tab[,1]/e2_alpha_tab[,2]
e2_alpha_tab[,4] <- 1 - pchisq(e2_alpha_tab[,3]**2,1)
}
}
e2_bas_tab <- NULL
if(x$control$hazard_baseline_CR == "Exponential"){
e2_bas_tab <- matrix(nrow = 1, ncol = 4)
e2_bas_tab[,1] <- alpha.CR[1]
e2_bas_tab[,2] <- alpha.CR.se[1]
e2_bas_tab[,3] <- e2_bas_tab[,1]/e2_bas_tab[,2]
e2_bas_tab[,4] <- 1 - pchisq(e2_bas_tab[,3]**2,1)
# e2_bas_tab[1,] <- e2_alpha_tab[1,]
# e2_alpha_tab <- e2_alpha_tab[-1,]
e2_names_tab <- c(e2_names_tab, alpha.CR.name[-1])
rownames(e2_bas_tab) <- c("intercept")
colnames(e2_bas_tab) <- c("Coeff", "SE", "Wald", "P-value")
}
if(x$control$hazard_baseline_CR == "Weibull"){
e2_bas_tab <- matrix(nrow = 2, ncol = 4)
#e2_bas_tab[1,] <- e2_alpha_tab[1,]
#e2_alpha_tab <- e2_alpha_tab[-1,]
e2_names_tab <- c(e2_names_tab, alpha.CR.name[-1])
e2_bas_tab[,1] <- alpha.CR[1]
e2_bas_tab[,2] <- alpha.CR.se[1]
e2_bas_tab[2,1] <- shape.CR
e2_bas_tab[2,2] <- shape.CR.se
e2_bas_tab[,3] <- e2_bas_tab[,1]/e2_bas_tab[,2]
e2_bas_tab[,4] <- 1 - pchisq(e2_bas_tab[,3]**2,1)
rownames(e2_bas_tab) <- c("intercept",shape.CR.name)
colnames(e2_bas_tab) <- c("Coeff", "SE", "Wald", "P-value")
}
if(x$control$hazard_baseline_CR == "Splines"){
e2_bas_tab <- matrix(nrow = length(gamma.CR), ncol = 4)
e2_bas_tab[,1] <- gamma.CR
e2_bas_tab[,2] <- gamma.CR.se
e2_bas_tab[,3] <- e2_bas_tab[,1]/e2_bas_tab[,2]
e2_bas_tab[,4] <- 1 - pchisq(e2_bas_tab[,3]**2,1)
rownames(e2_bas_tab) <- gamma.CR.name
colnames(e2_bas_tab) <- c("Coeff", "SE", "Wald", "P-value")
}
e2_surv_tab <- rbind(e2_var_tab, e2_share_current_tab, e2_share_slope_tab, e2_alpha_tab)
rownames(e2_surv_tab) <- e2_names_tab
colnames(e2_surv_tab) <- c("Coeff", "SE", "Wald", "P-value")
if(nrow(e2_bas_tab)!=0){
cat("\n")
cat(" Regression:")
cat("\n")
print(e2_surv_tab)
}
cat("\n")
cat(paste(" Baseline: ",x$control$hazard_baseline_CR), "\n")
cat("\n")
print(e2_bas_tab)
cat("\n")
}
}
Try the FlexVarJM package in your browser
Any scripts or data that you put into this service are public.
FlexVarJM documentation built on Nov. 21, 2023, 1:06 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Defines functions summary.lsjm
#' @export
summary.lsjm <- function(object,...)
{
x <- object
if(!inherits(x, "lsjm")) stop("use only \"lsjm\" objects")
cat("Joint model for quantitative outcome and competing risks", "\n")
cat("with heterogenous variability and fitted by maximum likelihood method", "\n")
#ajouter le code d'appelle à la fonction
cat("\n")
cat("Statistical Model:", "\n")
cat(paste(" Number of subjects:", x$control$Ind),"\n")
cat(paste(" Number of observations:", nrow(x$control$data.long)),"\n")
#cat(paste(" Number of events 1:", ),"\n")
#cat(paste(" Number of events 2:", ),"\n")
cat("\n")
cat("Iteration process:", "\n")
if(x$control$conv==1) cat(" Convergence criteria satisfied")
if(x$control$conv==2) cat(" Maximum number of iteration reached without convergence")
if(x$control$conv==4) {cat(" The program stopped abnormally. No results can be displayed. \n")
}
else{
cat("\n")
cat(paste(" Number of iterations: ",x$control$niter), "\n")
cat(paste(" Convergence criteria: parameters =" ,signif(x$control$convcrit[1],3)), "\n")
cat(paste(" : likelihood =" ,signif(x$control$convcrit[2],3)), "\n")
cat(paste(" : second derivatives =" ,signif(x$control$convcrit[3],3)), "\n")
cat(paste(" Time of computation :" ,format(x$time.compute)))
}
cat("\n")
cat("\n")
cat("Goodness-of-fit statistics:")
cat("\n")
cat(paste(" Likelihood: ", x$control$likelihood_value),"\n")
cat(paste(" AIC: ", 2*nrow(x$table.res) - 2* x$control$likelihood_value),"\n")
cat("\n")
cat("Maximum Likelihood Estimates:")
#Manage parameters
curseur <- 1
param <- x$table.res$Estimation
param.se <- x$table.res$SE
param.names <- rownames(x$table.res)
#browser()
#Evenement 1 :
## Risque de base :
if(x$control$hazard_baseline == "Weibull"){
#if(scaleWeibull == "square"){
# alpha_weib <- param[curseur]**2
# curseur <- curseur + 1
# shape <- param[curseur]**2
# curseur <- curseur + 1
#}
#else{
# alpha_weib <- exp(param[curseur])
# curseur <- curseur + 1
# shape <- exp(param[curseur])
# curseur <- curseur + 1
#}
shape <- param[curseur]
shape.se <- param.se[curseur]
shape.name <- param.names[curseur]
curseur <- curseur + 1
}
if(x$control$hazard_baseline == "Splines"){
gamma <- param[(curseur):(curseur+x$control$ord.splines+1)]
gamma.se <- param.se[(curseur):(curseur+x$control$ord.splines+1)]
gamma.name <- param.names[(curseur):(curseur+x$control$ord.splines+1)]
curseur <- curseur + x$control$ord.splines + 2
}
## Covariables :
if(x$control$nb.alpha >=1){
alpha <- param[(curseur):(curseur+x$control$nb.alpha-1)]
alpha.se <- param.se[(curseur):(curseur+x$control$nb.alpha-1)]
alpha.name <- param.names[(curseur):(curseur+x$control$nb.alpha-1)]
curseur <- curseur+x$control$nb.alpha
}
## Association :
if(c("random effect") %in% x$control$sharedtype ){
stop("Not implemented yet")
}
if(c("current value") %in% x$control$sharedtype){
alpha.current <- param[curseur]
alpha.current.se <- param.se[curseur]
alpha.current.name <- param.names[curseur]
curseur <- curseur + 1
}
if(c("slope") %in% x$control$sharedtype){
alpha.slope <- param[curseur]
alpha.slope.se <- param.se[curseur]
alpha.slope.name <- param.names[curseur]
curseur <- curseur + 1
}
if(c("variability") %in% x$control$sharedtype){
alpha.sigma <- param[curseur]
alpha.sigma.se <- param.se[curseur]
alpha.sigma.name <- param.names[curseur]
curseur <- curseur + 1
}
# Evenement 2
if(x$control$competing_risk){
## Risque de base :
if(x$control$hazard_baseline_CR == "Weibull"){
#if(scaleWeibull == "square"){
# alpha_weib.CR <- param[curseur]**2
# curseur <- curseur + 1
# shape.CR <- param[curseur]**2
# curseur <- curseur + 1
#}
#else{
# alpha_weib.CR <- exp(param[curseur])
# curseur <- curseur + 1
# shape.CR <- exp(param[curseur])
# curseur <- curseur + 1
#}
shape.CR <- param[curseur]
shape.CR.se <- param.se[curseur]
shape.CR.name <- param.names[curseur]
curseur <- curseur + 1
}
if(x$control$hazard_baseline_CR == "Splines"){
gamma.CR <- param[(curseur):(curseur+x$control$ord.splines+1)]
gamma.CR.se <- param.se[(curseur):(curseur+x$control$ord.splines+1)]
gamma.CR.name <- param.names[(curseur):(curseur+x$control$ord.splines+1)]
curseur <- curseur + x$control$ord.splines + 2
}
## Covariables :
if(x$control$nb.alpha.CR >=1){
alpha.CR <- param[(curseur):(curseur+x$control$nb.alpha.CR-1)]
alpha.CR.se <- param.se[(curseur):(curseur+x$control$nb.alpha.CR-1)]
alpha.CR.name <- param.names[(curseur):(curseur+x$control$nb.alpha.CR-1)]
curseur <- curseur+x$control$nb.alpha.CR
}
## Association :
if(c("random effect") %in% x$control$sharedtype_CR){
stop("Not implemented yet")
}
if(c("current value") %in% x$control$sharedtype_CR){
alpha.current.CR <- param[curseur]
alpha.current.CR.se <- param.se[curseur]
alpha.current.CR.name <- param.names[curseur]
curseur <- curseur + 1
}
if(c("slope") %in% x$control$sharedtype_CR){
alpha.slope.CR <- param[curseur]
alpha.slope.CR.se <- param.se[curseur]
alpha.slope.CR.name <- param.names[curseur]
curseur <- curseur + 1
}
if(c("variability") %in% x$control$sharedtype_CR){
alpha.sigma.CR <- param[curseur]
alpha.sigma.CR.se <- param.se[curseur]
alpha.sigma.CR.name <- param.names[curseur]
curseur <- curseur + 1
}
}
# Marqueur :
## Effets fixes trend :
beta <- param[curseur:(curseur+x$control$nb.priorMean.beta-1)]
beta.se <- param.se[curseur:(curseur+x$control$nb.priorMean.beta-1)]
beta.name <- param.names[curseur:(curseur+x$control$nb.priorMean.beta-1)]
curseur <- curseur+x$control$nb.priorMean.beta
## Effets fixes var :
if(x$control$variability_hetero){
omega <- param[curseur:(curseur+x$control$nb.omega-1)]
omega.se <- param.se[curseur:(curseur+x$control$nb.omega-1)]
omega.name <- param.names[curseur:(curseur+x$control$nb.omega-1)]
curseur <- curseur + x$control$nb.omega
}
else{
sigma.epsilon <- param[curseur]
sigma.epsilon.se <- param.se[curseur]
sigma.epsilon.name <- param.names[curseur]
curseur <- curseur + 1
}
## Matrice de variance-covariance de l'ensemble des effets aléatoires :
if(x$control$variability_hetero){
if(x$control$correlated_re){
borne1 <- curseur + choose(n = x$control$nb.e.a, k = 2) + x$control$nb.e.a - 1
C1 <- matrix(rep(0,(x$control$nb.e.a)**2),nrow=x$control$nb.e.a,ncol=x$control$nb.e.a)
C1[lower.tri(C1, diag=T)] <- param[curseur:borne1]
C2 <- matrix(param[(borne1+1):(borne1+x$control$nb.e.a.sigma*x$control$nb.e.a)],nrow=x$control$nb.e.a.sigma,ncol=x$control$nb.e.a, byrow = TRUE)
borne2 <- borne1+x$control$nb.e.a.sigma*x$control$nb.e.a + 1
borne3 <- borne2 + choose(n = x$control$nb.e.a.sigma, k = 2) + x$control$nb.e.a.sigma - 1
C3 <- matrix(rep(0,(x$control$nb.e.a.sigma)**2),nrow=x$control$nb.e.a.sigma,ncol=x$control$nb.e.a.sigma)
C3[lower.tri(C3, diag=T)] <- param[borne2:borne3]
C4 <- matrix(rep(0,x$control$nb.e.a*x$control$nb.e.a.sigma),nrow=x$control$nb.e.a,ncol=x$control$nb.e.a.sigma)
MatCov <- rbind(cbind(C1,C4),cbind(C2,C3))
MatCov <- as.matrix(MatCov)
}
else{
borne1 <- curseur + choose(n = x$control$nb.e.a, k = 2) + x$control$nb.e.a - 1
C1 <- matrix(rep(0,(x$control$nb.e.a)**2),nrow=x$control$nb.e.a,ncol=x$control$nb.e.a)
C1[lower.tri(C1, diag=T)] <- param[curseur:borne1]
borne3 <- borne1 + choose(n = x$control$nb.e.a.sigma, k = 2) + x$control$nb.e.a.sigma
C3 <- matrix(rep(0,(x$control$nb.e.a.sigma)**2),nrow=x$control$nb.e.a.sigma,ncol=x$control$nb.e.a.sigma)
C3[lower.tri(C3, diag=T)] <- param[(borne1+1):borne3]
C4 <- matrix(rep(0,x$control$nb.e.a*x$control$nb.e.a.sigma),nrow=x$control$nb.e.a,ncol=x$control$nb.e.a.sigma)
C2.bis <- matrix(rep(0,x$control$nb.e.a*x$control$nb.e.a.sigma),nrow=x$control$nb.e.a.sigma,ncol=x$control$nb.e.a)
MatCov <- rbind(cbind(C1,C4),cbind(C2.bis,C3))
MatCov <- as.matrix(MatCov)
}
}
else{
borne1 <- curseur + choose(n = x$control$nb.e.a, k = 2) + x$control$nb.e.a - 1
C1 <- matrix(rep(0,(x$control$nb.e.a)**2),nrow=x$control$nb.e.a,ncol=x$control$nb.e.a)
C1[lower.tri(C1, diag=T)] <- param[curseur:borne1]
MatCov <- C1
}
cat("\n")
cat("Longitudinal model:")
cat("\n")
cat(" Fixed effects:")
# betas_tab <- x$table.res[grep("^beta", rownames(x$table.res)),]
#print(rownames(betas_tab))
#r.name.betas <- strsplit(rownames(betas_tab), "#§#_")
#r.name.betas2 <- c()
#for(l in r.name.betas){
# r.name.betas2 <- c(r.name.betas2, l[-1])
#}
#print(r.name.betas2)
betas_tab <- matrix(nrow = length(beta), ncol = 4)
betas_tab[,1] <- beta
betas_tab[,2] <- beta.se
betas_tab[,3] <- betas_tab[,1]/betas_tab[,2]
betas_tab[,4] <- 1 - pchisq(betas_tab[,3]**2,1)
betas_tab <- as.data.frame(betas_tab)
rownames(betas_tab) <- beta.name
colnames(betas_tab) <- c("Coeff", "SE", "Wald", "P-value")
cat("\n")
print(betas_tab)
if(x$control$variability_hetero){
cat("\n")
cat(" Fixed effects of the linear predictor associated with variability:")
var_tab <- matrix(nrow = length(omega), ncol = 4)
var_tab[,1] <- omega
var_tab[,2] <- omega.se
var_tab[,3] <- var_tab[,1]/var_tab[,2]
var_tab[,4] <- 1 - pchisq(var_tab[,3]**2,1)
var_tab <- as.data.frame(var_tab)
rownames(var_tab) <- omega.name
colnames(var_tab) <- c("Coeff", "SE", "Wald", "P-value")
cat("\n")
print(var_tab)
}
else{
cat("\n")
var_tab <- matrix(nrow = length(sigma.epsilon), ncol = 4)
var_tab[,1] <- sigma.epsilon
var_tab[,2] <- sigma.epsilon.se
var_tab[,3] <- var_tab[,1]/var_tab[,2]
var_tab[,4] <- 1 - pchisq(var_tab[,3]**2,1)
var_tab <- as.data.frame(var_tab)
rownames(var_tab) <- sigma.epsilon.name
colnames(var_tab) <- c("Coeff", "SE", "Wald", "P-value")
cat("\n")
print(var_tab)
}
cat("\n")
cat(" Covariance matrix of the random effects:")
cat("\n")
#chol_mat <- x$table.res$Estimation[grep("^chol", rownames(x$table.res))]
#chol_mat2 <- matrix(0,nrow = quad(1,1,-2*length(chol_mat)), ncol = quad(1,1,-2*length(chol_mat)) )
#chol_mat2[lower.tri(chol_mat2, diag=T)] <- chol_mat
#print(chol_mat2,quote=FALSE,na.print="")
print(MatCov%*%t(MatCov),quote=FALSE,na.print="")
cat("\n")
cat("Survival model(s):")
cat("\n")
cat(" First event:")
#browser()
e1_var_tab <- NULL
e1_share_current_tab <- NULL
e1_share_slope_tab <- NULL
e1_alpha_tab <- NULL
e1_names_tab <- c()
#browser()
if(c("variability") %in% x$control$sharedtype){
e1_var_tab <- matrix(nrow = 1, ncol = 4)
e1_var_tab[,1] <- alpha.sigma
e1_var_tab[,2] <- alpha.sigma.se
e1_var_tab[,3] <- e1_var_tab[,1]/e1_var_tab[,2]
e1_var_tab[,4] <- 1 - pchisq(e1_var_tab[,3]**2,1)
e1_names_tab <- c(e1_names_tab, alpha.sigma.name)
}
if(c("random effect") %in% x$control$sharedtype){
print("Not implemented yet")
}
if(c("current value") %in% x$control$sharedtype){
e1_share_current_tab <- matrix(nrow = 1, ncol = 4)
e1_share_current_tab[,1] <- alpha.current
e1_share_current_tab[,2] <- alpha.current.se
e1_share_current_tab[,3] <- e1_share_current_tab[,1]/e1_share_current_tab[,2]
e1_share_current_tab[,4] <- 1 - pchisq(e1_share_current_tab[,3]**2,1)
e1_names_tab <- c(e1_names_tab, alpha.current.name)
}
#leonie la plus belle <3 <3 <3
if(c("slope") %in% x$control$sharedtype){
e1_share_slope_tab <- matrix(nrow = 1, ncol = 4)
e1_share_slope_tab[,1] <- c(alpha.slope)
e1_share_slope_tab[,2] <- c(alpha.slope.se)
e1_share_slope_tab[,3] <- e1_share_slope_tab[,1]/e1_share_slope_tab[,2]
e1_share_slope_tab[,4] <- 1 - pchisq(e1_share_slope_tab[,3]**2,1)
e1_names_tab <- c(e1_names_tab, alpha.slope.name)
}
if(x$control$hazard_baseline == "Splines"){
if(x$control$nb.alpha >=1){
e1_alpha_tab <- matrix(nrow = length(alpha), ncol = 4)
e1_alpha_tab[,1] <- alpha
e1_alpha_tab[,2] <- alpha.se
e1_alpha_tab[,3] <- e1_alpha_tab[,1]/e1_alpha_tab[,2]
e1_alpha_tab[,4] <- 1 - pchisq(e1_alpha_tab[,3]**2,1)
e1_names_tab <- c(e1_names_tab, alpha.name)
}
}
else{
if(x$control$nb.alpha >=2){
e1_alpha_tab <- matrix(nrow = length(alpha)-1, ncol = 4)
e1_alpha_tab[,1] <- alpha[-1]
e1_alpha_tab[,2] <- alpha.se[-1]
e1_alpha_tab[,3] <- e1_alpha_tab[,1]/e1_alpha_tab[,2]
e1_alpha_tab[,4] <- 1 - pchisq(e1_alpha_tab[,3]**2,1)
e1_names_tab <- c(e1_names_tab, alpha.name[-1])
}
}
e1_bas_tab <- NULL
if(x$control$hazard_baseline == "Exponential"){
e1_bas_tab <- matrix(nrow = 1, ncol = 4)
e1_bas_tab[1,1] <- alpha[1]
e1_bas_tab[1,2] <- alpha.se[1]
e1_bas_tab[1,3] <- e1_bas_tab[,1]/e1_bas_tab[,2]
e1_bas_tab[1,4] <- 1 - pchisq(e1_bas_tab[,3]**2,1)
#e1_alpha_tab <- e1_alpha_tab[-1,]
e1_names_tab <- c(e1_names_tab, alpha.name[-1])
rownames(e1_bas_tab) <- c("intercept")
colnames(e1_bas_tab) <- c("Coeff", "SE", "Wald", "P-value")
}
if(x$control$hazard_baseline == "Weibull"){
e1_bas_tab <- matrix(nrow = 2, ncol = 4)
e1_bas_tab[1,1] <- alpha[1]
e1_bas_tab[1,2] <- alpha.se[1]
#e1_bas_tab[1,] <- e1_alpha_tab[1,]
#e1_alpha_tab <- e1_alpha_tab[-1,]
#e1_names_tab <- c(e1_names_tab, alpha.name[-1])
e1_bas_tab[2,1] <- shape
e1_bas_tab[2,2] <- shape.se
e1_bas_tab[,3] <- e1_bas_tab[,1]/e1_bas_tab[,2]
e1_bas_tab[,4] <- 1 - pchisq(e1_bas_tab[,3]**2,1)
rownames(e1_bas_tab) <- c("intercept",shape.name)
colnames(e1_bas_tab) <- c("Coeff", "SE", "Wald", "P-value")
}
if(x$control$hazard_baseline == "Splines"){
e1_bas_tab <- matrix(nrow = length(gamma), ncol = 4)
e1_bas_tab[,1] <- gamma
e1_bas_tab[,2] <- gamma.se
e1_bas_tab[,3] <- e1_bas_tab[,1]/e1_bas_tab[,2]
e1_bas_tab[,4] <- 1 - pchisq(e1_bas_tab[,3]**2,1)
rownames(e1_bas_tab) <- gamma.name
colnames(e1_bas_tab) <- c("Coeff", "SE", "Wald", "P-value")
}
e1_surv_tab <- rbind(e1_var_tab, e1_share_current_tab, e1_share_slope_tab, e1_alpha_tab)
rownames(e1_surv_tab) <- e1_names_tab
colnames(e1_surv_tab) <- c("Coeff", "SE", "Wald", "P-value")
if(nrow(e1_bas_tab)!=0){
cat("\n")
cat(" Regression:")
cat("\n")
print(e1_surv_tab)
}
cat("\n")
cat(paste(" Baseline: ",x$control$hazard_baseline), "\n")
cat("\n")
print(e1_bas_tab)
cat("\n")
if(x$control$competing_risk){
cat(" Second event:")
e2_var_tab <- NULL
e2_share_current_tab <- NULL
e2_share_slope_tab <- NULL
e2_alpha_tab <- NULL
e2_names_tab <- c()
if(c("variability") %in% x$control$sharedtype_CR){
e2_var_tab <- matrix(nrow = 1, ncol = 4)
e2_var_tab[,1] <- alpha.sigma.CR
e2_var_tab[,2] <- alpha.sigma.CR.se
e2_var_tab[,3] <- e2_var_tab[,1]/e2_var_tab[,2]
e2_var_tab[,4] <- 1 - pchisq(e2_var_tab[,3]**2,1)
e2_names_tab <- c(e2_names_tab, alpha.sigma.CR.name)
}
if(c("random effect") %in% x$control$sharedtype_CR){
print("Not implemented yet")
}
if(c("current value") %in% x$control$sharedtype_CR){
e2_share_current_tab <- matrix(nrow = 1, ncol = 4)
e2_share_current_tab[,1] <- alpha.current.CR
e2_share_current_tab[,2] <- alpha.current.CR.se
e2_share_current_tab[,3] <- e2_share_current_tab[,1]/e2_share_current_tab[,2]
e2_share_current_tab[,4] <- 1 - pchisq(e2_share_current_tab[,3]**2,1)
e2_names_tab <- c(e2_names_tab, alpha.current.CR.name)
}
if(c("slope") %in% x$control$sharedtype_CR){
e2_share_slope_tab <- matrix(nrow = 1, ncol = 4)
e2_share_slope_tab[,1] <- alpha.slope.CR
e2_share_slope_tab[,2] <- alpha.slope.CR.se
e2_share_slope_tab[,3] <- e2_share_slope_tab[,1]/e2_share_slope_tab[,2]
e2_share_slope_tab[,4] <- 1 - pchisq(e2_share_slope_tab[,3]**2,1)
e2_names_tab <- c(e2_names_tab, alpha.slope.CR.name)
}
if(x$control$hazard_baseline_CR == "Splines"){
if(x$control$nb.alpha.CR >=1){
e2_alpha_tab <- matrix(nrow = length(alpha.CR), ncol = 4)
e2_alpha_tab[,1] <- alpha.CR
e2_alpha_tab[,2] <- alpha.CR.se
e2_alpha_tab[,3] <- e2_alpha_tab[,1]/e2_alpha_tab[,2]
e2_alpha_tab[,4] <- 1 - pchisq(e2_alpha_tab[,3]**2,1)
}
}
else{
if(x$control$nb.alpha.CR >=2){
e2_alpha_tab <- matrix(nrow = length(alpha.CR)-1, ncol = 4)
e2_alpha_tab[,1] <- alpha.CR[-1]
e2_alpha_tab[,2] <- alpha.CR.se[-1]
e2_alpha_tab[,3] <- e2_alpha_tab[,1]/e2_alpha_tab[,2]
e2_alpha_tab[,4] <- 1 - pchisq(e2_alpha_tab[,3]**2,1)
}
}
e2_bas_tab <- NULL
if(x$control$hazard_baseline_CR == "Exponential"){
e2_bas_tab <- matrix(nrow = 1, ncol = 4)
e2_bas_tab[,1] <- alpha.CR[1]
e2_bas_tab[,2] <- alpha.CR.se[1]
e2_bas_tab[,3] <- e2_bas_tab[,1]/e2_bas_tab[,2]
e2_bas_tab[,4] <- 1 - pchisq(e2_bas_tab[,3]**2,1)
# e2_bas_tab[1,] <- e2_alpha_tab[1,]
# e2_alpha_tab <- e2_alpha_tab[-1,]
e2_names_tab <- c(e2_names_tab, alpha.CR.name[-1])
rownames(e2_bas_tab) <- c("intercept")
colnames(e2_bas_tab) <- c("Coeff", "SE", "Wald", "P-value")
}
if(x$control$hazard_baseline_CR == "Weibull"){
e2_bas_tab <- matrix(nrow = 2, ncol = 4)
#e2_bas_tab[1,] <- e2_alpha_tab[1,]
#e2_alpha_tab <- e2_alpha_tab[-1,]
e2_names_tab <- c(e2_names_tab, alpha.CR.name[-1])
e2_bas_tab[,1] <- alpha.CR[1]
e2_bas_tab[,2] <- alpha.CR.se[1]
e2_bas_tab[2,1] <- shape.CR
e2_bas_tab[2,2] <- shape.CR.se
e2_bas_tab[,3] <- e2_bas_tab[,1]/e2_bas_tab[,2]
e2_bas_tab[,4] <- 1 - pchisq(e2_bas_tab[,3]**2,1)
rownames(e2_bas_tab) <- c("intercept",shape.CR.name)
colnames(e2_bas_tab) <- c("Coeff", "SE", "Wald", "P-value")
}
if(x$control$hazard_baseline_CR == "Splines"){
e2_bas_tab <- matrix(nrow = length(gamma.CR), ncol = 4)
e2_bas_tab[,1] <- gamma.CR
e2_bas_tab[,2] <- gamma.CR.se
e2_bas_tab[,3] <- e2_bas_tab[,1]/e2_bas_tab[,2]
e2_bas_tab[,4] <- 1 - pchisq(e2_bas_tab[,3]**2,1)
rownames(e2_bas_tab) <- gamma.CR.name
colnames(e2_bas_tab) <- c("Coeff", "SE", "Wald", "P-value")
}
e2_surv_tab <- rbind(e2_var_tab, e2_share_current_tab, e2_share_slope_tab, e2_alpha_tab)
rownames(e2_surv_tab) <- e2_names_tab
colnames(e2_surv_tab) <- c("Coeff", "SE", "Wald", "P-value")
if(nrow(e2_bas_tab)!=0){
cat("\n")
cat(" Regression:")
cat("\n")
print(e2_surv_tab)
}
cat("\n")
cat(paste(" Baseline: ",x$control$hazard_baseline_CR), "\n")
cat("\n")
print(e2_bas_tab)
cat("\n")
}
}
Try the FlexVarJM package in your browser
Any scripts or data that you put into this service are public.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.