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#' @title Log-likelihood function for log-normal distribution with cured population
#' @description Provide log-likelihood function for log-normal distribution with cured population
#'
#' @param df The subject-level event data, including \code{time}
#' and \code{event}.
#' @param par a vector with three elements, where the first element denotes the logistic of the proportion
#' of the cured population, and the second element and the third element denote
#' the mean and the log of standard deviation parameter of the log-normal distribution.
#'
#' @return
#' The negative value of the log-likelihood function given parameter
#' \code{par} and the dataset \code{df}
#'
#' @references
#' \itemize{
#' \item Chen, Tai-Tsang. "Predicting analysis times in randomized clinical trials with cancer immunotherapy."
#' BMC medical research methodology 16.1 (2016): 1-10.
#' }
#'
#'
#' @export
#'
#'
#'
loglik_Chen_log_normal<-function(par,df){
p=exp(par[1])/(1+exp(par[1]))
mu=par[2]
sigma=exp(par[3])
delta=df$event
t=df$time
f0=1/(sqrt(2*pi)*sigma*t)*exp(-(log(t)-mu)^2/(2*sigma^2))
S0=1-stats::pnorm(log(t),mean=mu,sd=sigma)
part1=delta*(log(1-p)+log(f0))
part2=(1-delta)*log(p+(1-p)*S0)
neg_loglik=-sum(part1+part2)
return(neg_loglik)
}
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