R/tvcFlex.R
In ywang297/CoxFlex: Flexible Modeling of the Time-to-Event Data
#' Estimate the TD and/or NL effect(s) of time-varying continuous covariate(s) in time-to-event analysis
#'
#' @param data A data frame in the long (interval) format with one line per unit of time.
#' @param Type A vector consisting the name of variables representing the start/stop of each
#' time interval, event indicator, and names of variable representing the TEL of each sparsely
#' mearused time-varying covariates. e.g. c("start","stop","event","tel").
#' @param variables A vector consisting the name of varialbes that will be adjusted in the model.
#' @param TD A vector of binary indicators representing whether the corresponding variable has a time-dependent
#' effect or not (1=Yes, 0=No).
#' @param NL A vector of binary indicators representing whether the corresponding variable has a non-linear
#' effect or not (1=Yes, 0=No).
#' @param TEL A vector of binary indicators representing whether to adjust the TEL effect of the corresponding variable
#' (1=Yes, 0=No).
#' @param m The number of interior knots used in the regression B-spline
#' @param p The degree of the regression B-spline
#' @param knots Default value is -999, set the knots at the default place.
#' @return Returns a list of the following items:
#' @return \item{PLL}{ partial loglikelihood of the final model}
#' \item{NP}{ number of parameters estimated in the model}
#' \item{NE}{ number of events in the dataset}
#' \item{knots_covariates}{knots for splines of NL effects for corresponding covariates}
#' \item{knots_time}{knots for splines of the TD effect}
#' \item{knots_TEL}{knots for splines of the TEL effect}
#' \item{variables}{name of the covariates in the order they are adjusted in the model}
#' \item{coefficients_splines_NL}{estimated splines coefficients for NL effects}
#' \item{coefficients_splines_TD}{estimated splines coefficients for TD effects}
#' \item{coefficients_splines_TEL}{estimated splines coefficients for TEL effects}
#' \item{coef}{estimated coefficients for covariates not having TD and NL effects}
#' \item{sd}{standard errors of the corresponding estimated coefficients}
#' \item{pval}{p-values for corresponding estimated effects}
#'@note Note that the TD and NL arguments have different meanings than that in the \code{\link{BackSelection}}
#' @export
tvcFlex<-function (data, Type, variables, TD, NL,TEL, m, p,knots) {
if (sum(TEL)==0){
CoxFlex(data,Type,variables,TD,NL,m,p,knots)
} else{
res_principal<-last_prog_TEL(data, Type, variables, TD, NL,TEL ,m, p,knots)
TDtestP<-rep(-999,length(variables))
TDtestN<-rep(-999,length(variables))
TDtest<-rep(-999,length(variables))
TDdev<-rep(-999,length(variables))
NLtestP<-rep(-999,length(variables))
NLtestN<-rep(-999,length(variables))
NLtest<-rep(-999,length(variables))
NLdev<-rep(-999,length(variables))
TELtestP<-rep(-999,length(variables))
TELtestN<-rep(-999,length(variables))
TELtest<-rep(-999,length(variables))
TELdev<-rep(-999,length(variables))
for (kt in 1:length(variables)){
if (TD[kt]==1){
TDnew<-TD
TDnew[kt]<-0
resSEC<-last_prog_TEL(data, Type, variables, TDnew, NL,TEL, m, p,knots)
TDtestP[kt]<-resSEC$Partial_Log_Likelihood
TDtestN[kt]<-resSEC$Number_of_parameters
TDtest[kt]<-1-stats::pchisq(-2*(TDtestP[kt]-res_principal$Partial_Log_Likelihood),res_principal$Number_of_parameters-TDtestN[kt])
TDdev[kt]<--2*(TDtestP[kt]-res_principal$Partial_Log_Likelihood)
}
if (NL[kt]==1){
NLnew<-NL
NLnew[kt]<-0
resSEC<-last_prog_TEL(data, Type, variables, TD, NLnew,TEL, m, p,knots)
NLtestP[kt]<-resSEC$Partial_Log_Likelihood
NLtestN[kt]<-resSEC$Number_of_parameters
NLtest[kt]<-1-stats::pchisq(-2*(NLtestP[kt]-res_principal$Partial_Log_Likelihood),res_principal$Number_of_parameters-NLtestN[kt])
NLdev[kt]<--2*(NLtestP[kt]-res_principal$Partial_Log_Likelihood)
}
if (TEL[kt]==1){
TELnew<-TEL
TELnew[kt]<-0
resSEC<-last_prog_TEL(data, Type, variables, TD, NL,TELnew, m, p,knots)
TELtestP[kt]<-resSEC$Partial_Log_Likelihood
TELtestN[kt]<-resSEC$Number_of_parameters
TELtest[kt]<-1-stats::pchisq(-2*(TELtestP[kt]-res_principal$Partial_Log_Likelihood),res_principal$Number_of_parameters-TELtestN[kt])
TELdev[kt]<--2*(TELtestP[kt]-res_principal$Partial_Log_Likelihood)
}
}
Rescox<-matrix(ncol=7,nrow=sum(3*(NL+TD+TEL==3)+2*(NL+TD+TEL==2)+1*(NL+TD+TEL!=2 & NL+TD+TEL!=3 )) )
colnames(Rescox)<-c("","coef","exp(coef)","se(coef)","z","p","dev")
rownames(Rescox)<-rep(c(""),sum(3*(NL+TD+TEL==3)+2*(NL+TD+TEL==2)+1*(NL+TD+TEL!=2 & NL+TD+TEL!=3 )))
indexrescox<-0
for (yu in 1:length(variables)){
indexrescox<-indexrescox+1
if (TD[yu]==0 & NL[yu]==0 & TEL[yu]==0){
Rescox[indexrescox,1]<-variables[yu]
Rescox[indexrescox,2]<-round(as.numeric(res_principal$coefficients[yu]),3)
Rescox[indexrescox,3]<-round(as.numeric(exp(res_principal$coefficients[yu])),3)
Rescox[indexrescox,4]<-round(as.numeric(res_principal$Standard_Error[yu]),3)
Rescox[indexrescox,5]<-round(as.numeric(res_principal$coefficients[yu]/res_principal$Standard_Error[yu]),3)
Rescox[indexrescox,6]<-round(as.numeric(1-stats::pchisq((res_principal$coefficients[yu]/res_principal$Standard_Error[yu])^2,df=1)) ,3)
Rescox[indexrescox,7]<-res_principal$Partial_Log_Likelihood
}
if (TD[yu]==0 & NL[yu]==1 & TEL[yu]==0){
Rescox[indexrescox,1]<-paste("NL(",variables[yu],")",sep="")
Rescox[indexrescox,2]<-"---"
Rescox[indexrescox,3]<-"splines"
Rescox[indexrescox,4]<-"---"
Rescox[indexrescox,5]<-"---"
Rescox[indexrescox,6]<-round(NLtest[yu],3)
Rescox[indexrescox,7]<-round(NLdev[yu],4)
}
if (TD[yu]==1 & NL[yu]==0 & TEL[yu]==0){
Rescox[indexrescox,1]<-paste("TD(",variables[yu],")",sep="")
Rescox[indexrescox,2]<-"---"
Rescox[indexrescox,3]<-"splines"
Rescox[indexrescox,4]<-"---"
Rescox[indexrescox,5]<-"---"
Rescox[indexrescox,6]<-round(TDtest[yu],3)
Rescox[indexrescox,7]<-round(TDdev[yu],4)
}
if (TD[yu]==0 & NL[yu]==0 & TEL[yu]==1){
Rescox[indexrescox,1]<-paste("TEL(",variables[yu],")",sep="")
Rescox[indexrescox,2]<-"---"
Rescox[indexrescox,3]<-"splines"
Rescox[indexrescox,4]<-"---"
Rescox[indexrescox,5]<-"---"
Rescox[indexrescox,6]<-round(TELtest[yu],3)
Rescox[indexrescox,7]<-round(TELdev[yu],4)
}
if (TD[yu]==1 & NL[yu]==1 & TEL[yu]==1){
Rescox[indexrescox,1]<-paste("NL(",variables[yu],")",sep="")
Rescox[indexrescox,2]<-"---"
Rescox[indexrescox,3]<-"splines"
Rescox[indexrescox,4]<-"---"
Rescox[indexrescox,5]<-"---"
Rescox[indexrescox,6]<-round(NLtest[yu],3)
Rescox[indexrescox,7]<-round(NLdev[yu],4)
indexrescox<-indexrescox+1
Rescox[indexrescox,1]<-paste("TD(",variables[yu],")",sep="")
Rescox[indexrescox,2]<-"---"
Rescox[indexrescox,3]<-"splines"
Rescox[indexrescox,4]<-"---"
Rescox[indexrescox,5]<-"---"
Rescox[indexrescox,6]<-round(TDtest[yu],3)
Rescox[indexrescox,7]<-round(TDdev[yu],4)
indexrescox<-indexrescox+1
Rescox[indexrescox,1]<-paste("TEL(",variables[yu],")",sep="")
Rescox[indexrescox,2]<-"---"
Rescox[indexrescox,3]<-"splines"
Rescox[indexrescox,4]<-"---"
Rescox[indexrescox,5]<-"---"
Rescox[indexrescox,6]<-round(TELtest[yu],3)
Rescox[indexrescox,7]<-round(TELdev[yu],4)
}
if (TD[yu]==1 & NL[yu]==1 & TEL[yu]==0){
Rescox[indexrescox,1]<-paste("NL(",variables[yu],")",sep="")
Rescox[indexrescox,2]<-"---"
Rescox[indexrescox,3]<-"splines"
Rescox[indexrescox,4]<-"---"
Rescox[indexrescox,5]<-"---"
Rescox[indexrescox,6]<-round(NLtest[yu],3)
Rescox[indexrescox,7]<-round(NLdev[yu],4)
indexrescox<-indexrescox+1
Rescox[indexrescox,1]<-paste("TD(",variables[yu],")",sep="")
Rescox[indexrescox,2]<-"---"
Rescox[indexrescox,3]<-"splines"
Rescox[indexrescox,4]<-"---"
Rescox[indexrescox,5]<-"---"
Rescox[indexrescox,6]<-round(TDtest[yu],3)
Rescox[indexrescox,7]<-round(TDdev[yu],4)
}
if (TD[yu]==0 & NL[yu]==1 & TEL[yu]==1){
Rescox[indexrescox,1]<-paste("NL(",variables[yu],")",sep="")
Rescox[indexrescox,2]<-"---"
Rescox[indexrescox,3]<-"splines"
Rescox[indexrescox,4]<-"---"
Rescox[indexrescox,5]<-"---"
Rescox[indexrescox,6]<-round(NLtest[yu],3)
Rescox[indexrescox,7]<-round(NLdev[yu],4)
indexrescox<-indexrescox+1
Rescox[indexrescox,1]<-paste("TEL(",variables[yu],")",sep="")
Rescox[indexrescox,2]<-"---"
Rescox[indexrescox,3]<-"splines"
Rescox[indexrescox,4]<-"---"
Rescox[indexrescox,5]<-"---"
Rescox[indexrescox,6]<-round(TELtest[yu],3)
Rescox[indexrescox,7]<-round(TELdev[yu],4)
}
if (TD[yu]==1 & NL[yu]==0 & TEL[yu]==1){
Rescox[indexrescox,1]<-paste("TD(",variables[yu],")",sep="")
Rescox[indexrescox,2]<-"---"
Rescox[indexrescox,3]<-"splines"
Rescox[indexrescox,4]<-"---"
Rescox[indexrescox,5]<-"---"
Rescox[indexrescox,6]<-round(TDtest[yu],3)
Rescox[indexrescox,7]<-round(TDdev[yu],4)
indexrescox<-indexrescox+1
Rescox[indexrescox,1]<-paste("TEL(",variables[yu],")",sep="")
Rescox[indexrescox,2]<-"---"
Rescox[indexrescox,3]<-"splines"
Rescox[indexrescox,4]<-"---"
Rescox[indexrescox,5]<-"---"
Rescox[indexrescox,6]<-round(TELtest[yu],3)
Rescox[indexrescox,7]<-round(TELdev[yu],4)
}
}
list(PLL= res_principal$Partial_Log_Likelihood,
NP= res_principal$Number_of_parameters,
NE=res_principal$Number_events,
knots_covariates = res_principal$knots_covariates,
knots_time = res_principal$knots_time,
knots_TEL = res_principal$knots_TEL,
variables=res_principal$variables,
# coefficients = res_principal$coefficients, Standard_Error=res_principal$Standard_Error,
coefficients_splines_NL = res_principal$coefficients_splines_NL,
coefficients_splines_TD = res_principal$coefficients_splines_TD,
coefficients_splines_TEL = res_principal$coefficients_splines_TEL,
coef=suppressWarnings(as.numeric(Rescox[,2])),
sd=suppressWarnings((as.numeric(Rescox[,4]))),
pvalue=suppressWarnings(as.numeric(Rescox[,6])))
# dev=suppressWarnings(as.numeric(Rescox[,7])))
}
}
ywang297/CoxFlex documentation built on March 18, 2024, 3:26 a.m.
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#' Estimate the TD and/or NL effect(s) of time-varying continuous covariate(s) in time-to-event analysis
#'
#' @param data A data frame in the long (interval) format with one line per unit of time.
#' @param Type A vector consisting the name of variables representing the start/stop of each
#' time interval, event indicator, and names of variable representing the TEL of each sparsely
#' mearused time-varying covariates. e.g. c("start","stop","event","tel").
#' @param variables A vector consisting the name of varialbes that will be adjusted in the model.
#' @param TD A vector of binary indicators representing whether the corresponding variable has a time-dependent
#' effect or not (1=Yes, 0=No).
#' @param NL A vector of binary indicators representing whether the corresponding variable has a non-linear
#' effect or not (1=Yes, 0=No).
#' @param TEL A vector of binary indicators representing whether to adjust the TEL effect of the corresponding variable
#' (1=Yes, 0=No).
#' @param m The number of interior knots used in the regression B-spline
#' @param p The degree of the regression B-spline
#' @param knots Default value is -999, set the knots at the default place.
#' @return Returns a list of the following items:
#' @return \item{PLL}{ partial loglikelihood of the final model}
#' \item{NP}{ number of parameters estimated in the model}
#' \item{NE}{ number of events in the dataset}
#' \item{knots_covariates}{knots for splines of NL effects for corresponding covariates}
#' \item{knots_time}{knots for splines of the TD effect}
#' \item{knots_TEL}{knots for splines of the TEL effect}
#' \item{variables}{name of the covariates in the order they are adjusted in the model}
#' \item{coefficients_splines_NL}{estimated splines coefficients for NL effects}
#' \item{coefficients_splines_TD}{estimated splines coefficients for TD effects}
#' \item{coefficients_splines_TEL}{estimated splines coefficients for TEL effects}
#' \item{coef}{estimated coefficients for covariates not having TD and NL effects}
#' \item{sd}{standard errors of the corresponding estimated coefficients}
#' \item{pval}{p-values for corresponding estimated effects}
#'@note Note that the TD and NL arguments have different meanings than that in the \code{\link{BackSelection}}
#' @export
tvcFlex<-function (data, Type, variables, TD, NL,TEL, m, p,knots) {
if (sum(TEL)==0){
CoxFlex(data,Type,variables,TD,NL,m,p,knots)
} else{
res_principal<-last_prog_TEL(data, Type, variables, TD, NL,TEL ,m, p,knots)
TDtestP<-rep(-999,length(variables))
TDtestN<-rep(-999,length(variables))
TDtest<-rep(-999,length(variables))
TDdev<-rep(-999,length(variables))
NLtestP<-rep(-999,length(variables))
NLtestN<-rep(-999,length(variables))
NLtest<-rep(-999,length(variables))
NLdev<-rep(-999,length(variables))
TELtestP<-rep(-999,length(variables))
TELtestN<-rep(-999,length(variables))
TELtest<-rep(-999,length(variables))
TELdev<-rep(-999,length(variables))
for (kt in 1:length(variables)){
if (TD[kt]==1){
TDnew<-TD
TDnew[kt]<-0
resSEC<-last_prog_TEL(data, Type, variables, TDnew, NL,TEL, m, p,knots)
TDtestP[kt]<-resSEC$Partial_Log_Likelihood
TDtestN[kt]<-resSEC$Number_of_parameters
TDtest[kt]<-1-stats::pchisq(-2*(TDtestP[kt]-res_principal$Partial_Log_Likelihood),res_principal$Number_of_parameters-TDtestN[kt])
TDdev[kt]<--2*(TDtestP[kt]-res_principal$Partial_Log_Likelihood)
}
if (NL[kt]==1){
NLnew<-NL
NLnew[kt]<-0
resSEC<-last_prog_TEL(data, Type, variables, TD, NLnew,TEL, m, p,knots)
NLtestP[kt]<-resSEC$Partial_Log_Likelihood
NLtestN[kt]<-resSEC$Number_of_parameters
NLtest[kt]<-1-stats::pchisq(-2*(NLtestP[kt]-res_principal$Partial_Log_Likelihood),res_principal$Number_of_parameters-NLtestN[kt])
NLdev[kt]<--2*(NLtestP[kt]-res_principal$Partial_Log_Likelihood)
}
if (TEL[kt]==1){
TELnew<-TEL
TELnew[kt]<-0
resSEC<-last_prog_TEL(data, Type, variables, TD, NL,TELnew, m, p,knots)
TELtestP[kt]<-resSEC$Partial_Log_Likelihood
TELtestN[kt]<-resSEC$Number_of_parameters
TELtest[kt]<-1-stats::pchisq(-2*(TELtestP[kt]-res_principal$Partial_Log_Likelihood),res_principal$Number_of_parameters-TELtestN[kt])
TELdev[kt]<--2*(TELtestP[kt]-res_principal$Partial_Log_Likelihood)
}
}
Rescox<-matrix(ncol=7,nrow=sum(3*(NL+TD+TEL==3)+2*(NL+TD+TEL==2)+1*(NL+TD+TEL!=2 & NL+TD+TEL!=3 )) )
colnames(Rescox)<-c("","coef","exp(coef)","se(coef)","z","p","dev")
rownames(Rescox)<-rep(c(""),sum(3*(NL+TD+TEL==3)+2*(NL+TD+TEL==2)+1*(NL+TD+TEL!=2 & NL+TD+TEL!=3 )))
indexrescox<-0
for (yu in 1:length(variables)){
indexrescox<-indexrescox+1
if (TD[yu]==0 & NL[yu]==0 & TEL[yu]==0){
Rescox[indexrescox,1]<-variables[yu]
Rescox[indexrescox,2]<-round(as.numeric(res_principal$coefficients[yu]),3)
Rescox[indexrescox,3]<-round(as.numeric(exp(res_principal$coefficients[yu])),3)
Rescox[indexrescox,4]<-round(as.numeric(res_principal$Standard_Error[yu]),3)
Rescox[indexrescox,5]<-round(as.numeric(res_principal$coefficients[yu]/res_principal$Standard_Error[yu]),3)
Rescox[indexrescox,6]<-round(as.numeric(1-stats::pchisq((res_principal$coefficients[yu]/res_principal$Standard_Error[yu])^2,df=1)) ,3)
Rescox[indexrescox,7]<-res_principal$Partial_Log_Likelihood
}
if (TD[yu]==0 & NL[yu]==1 & TEL[yu]==0){
Rescox[indexrescox,1]<-paste("NL(",variables[yu],")",sep="")
Rescox[indexrescox,2]<-"---"
Rescox[indexrescox,3]<-"splines"
Rescox[indexrescox,4]<-"---"
Rescox[indexrescox,5]<-"---"
Rescox[indexrescox,6]<-round(NLtest[yu],3)
Rescox[indexrescox,7]<-round(NLdev[yu],4)
}
if (TD[yu]==1 & NL[yu]==0 & TEL[yu]==0){
Rescox[indexrescox,1]<-paste("TD(",variables[yu],")",sep="")
Rescox[indexrescox,2]<-"---"
Rescox[indexrescox,3]<-"splines"
Rescox[indexrescox,4]<-"---"
Rescox[indexrescox,5]<-"---"
Rescox[indexrescox,6]<-round(TDtest[yu],3)
Rescox[indexrescox,7]<-round(TDdev[yu],4)
}
if (TD[yu]==0 & NL[yu]==0 & TEL[yu]==1){
Rescox[indexrescox,1]<-paste("TEL(",variables[yu],")",sep="")
Rescox[indexrescox,2]<-"---"
Rescox[indexrescox,3]<-"splines"
Rescox[indexrescox,4]<-"---"
Rescox[indexrescox,5]<-"---"
Rescox[indexrescox,6]<-round(TELtest[yu],3)
Rescox[indexrescox,7]<-round(TELdev[yu],4)
}
if (TD[yu]==1 & NL[yu]==1 & TEL[yu]==1){
Rescox[indexrescox,1]<-paste("NL(",variables[yu],")",sep="")
Rescox[indexrescox,2]<-"---"
Rescox[indexrescox,3]<-"splines"
Rescox[indexrescox,4]<-"---"
Rescox[indexrescox,5]<-"---"
Rescox[indexrescox,6]<-round(NLtest[yu],3)
Rescox[indexrescox,7]<-round(NLdev[yu],4)
indexrescox<-indexrescox+1
Rescox[indexrescox,1]<-paste("TD(",variables[yu],")",sep="")
Rescox[indexrescox,2]<-"---"
Rescox[indexrescox,3]<-"splines"
Rescox[indexrescox,4]<-"---"
Rescox[indexrescox,5]<-"---"
Rescox[indexrescox,6]<-round(TDtest[yu],3)
Rescox[indexrescox,7]<-round(TDdev[yu],4)
indexrescox<-indexrescox+1
Rescox[indexrescox,1]<-paste("TEL(",variables[yu],")",sep="")
Rescox[indexrescox,2]<-"---"
Rescox[indexrescox,3]<-"splines"
Rescox[indexrescox,4]<-"---"
Rescox[indexrescox,5]<-"---"
Rescox[indexrescox,6]<-round(TELtest[yu],3)
Rescox[indexrescox,7]<-round(TELdev[yu],4)
}
if (TD[yu]==1 & NL[yu]==1 & TEL[yu]==0){
Rescox[indexrescox,1]<-paste("NL(",variables[yu],")",sep="")
Rescox[indexrescox,2]<-"---"
Rescox[indexrescox,3]<-"splines"
Rescox[indexrescox,4]<-"---"
Rescox[indexrescox,5]<-"---"
Rescox[indexrescox,6]<-round(NLtest[yu],3)
Rescox[indexrescox,7]<-round(NLdev[yu],4)
indexrescox<-indexrescox+1
Rescox[indexrescox,1]<-paste("TD(",variables[yu],")",sep="")
Rescox[indexrescox,2]<-"---"
Rescox[indexrescox,3]<-"splines"
Rescox[indexrescox,4]<-"---"
Rescox[indexrescox,5]<-"---"
Rescox[indexrescox,6]<-round(TDtest[yu],3)
Rescox[indexrescox,7]<-round(TDdev[yu],4)
}
if (TD[yu]==0 & NL[yu]==1 & TEL[yu]==1){
Rescox[indexrescox,1]<-paste("NL(",variables[yu],")",sep="")
Rescox[indexrescox,2]<-"---"
Rescox[indexrescox,3]<-"splines"
Rescox[indexrescox,4]<-"---"
Rescox[indexrescox,5]<-"---"
Rescox[indexrescox,6]<-round(NLtest[yu],3)
Rescox[indexrescox,7]<-round(NLdev[yu],4)
indexrescox<-indexrescox+1
Rescox[indexrescox,1]<-paste("TEL(",variables[yu],")",sep="")
Rescox[indexrescox,2]<-"---"
Rescox[indexrescox,3]<-"splines"
Rescox[indexrescox,4]<-"---"
Rescox[indexrescox,5]<-"---"
Rescox[indexrescox,6]<-round(TELtest[yu],3)
Rescox[indexrescox,7]<-round(TELdev[yu],4)
}
if (TD[yu]==1 & NL[yu]==0 & TEL[yu]==1){
Rescox[indexrescox,1]<-paste("TD(",variables[yu],")",sep="")
Rescox[indexrescox,2]<-"---"
Rescox[indexrescox,3]<-"splines"
Rescox[indexrescox,4]<-"---"
Rescox[indexrescox,5]<-"---"
Rescox[indexrescox,6]<-round(TDtest[yu],3)
Rescox[indexrescox,7]<-round(TDdev[yu],4)
indexrescox<-indexrescox+1
Rescox[indexrescox,1]<-paste("TEL(",variables[yu],")",sep="")
Rescox[indexrescox,2]<-"---"
Rescox[indexrescox,3]<-"splines"
Rescox[indexrescox,4]<-"---"
Rescox[indexrescox,5]<-"---"
Rescox[indexrescox,6]<-round(TELtest[yu],3)
Rescox[indexrescox,7]<-round(TELdev[yu],4)
}
}
list(PLL= res_principal$Partial_Log_Likelihood,
NP= res_principal$Number_of_parameters,
NE=res_principal$Number_events,
knots_covariates = res_principal$knots_covariates,
knots_time = res_principal$knots_time,
knots_TEL = res_principal$knots_TEL,
variables=res_principal$variables,
# coefficients = res_principal$coefficients, Standard_Error=res_principal$Standard_Error,
coefficients_splines_NL = res_principal$coefficients_splines_NL,
coefficients_splines_TD = res_principal$coefficients_splines_TD,
coefficients_splines_TEL = res_principal$coefficients_splines_TEL,
coef=suppressWarnings(as.numeric(Rescox[,2])),
sd=suppressWarnings((as.numeric(Rescox[,4]))),
pvalue=suppressWarnings(as.numeric(Rescox[,6])))
# dev=suppressWarnings(as.numeric(Rescox[,7])))
}
}
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