R/return.ss.ng.int.req.r

In GNGTools: Tools for Go/No-Go Decision-Making Framework

#' @title Return single sample normal-gamma predictive probability
#'
#' @param mu.0.t prior mean for treatment group
#' @param alpha.0.t prior alpha parameter for treatment group
#' @param beta.0.t prior beta parameter for treatment group
#' @param n.0.t prior effective sample size for treatment group
#' @param xbar.t sample mean for treatment group
#' @param s.t sample sd for treatment group
#' @param interim.n.t interim sample size
#' @param final.n.t final sample size
#' @param Delta.tv Base TPP
#' @param Delta.lrv Min TPP
#' @param tau.tv threshold associated with Base TPP
#' @param tau.lrv threshold associated with Min TPP
#' @param tau.ng threshold associated with No-Go
#' @param xbar_ng xbar for no-go; leave null for standard rule
#' @param xbar_go xbar for go; leave null for standard rule
#' @param go.thresh go threshold for predictive probability
#' @param ng.thresh no-go threshold for predictive probability
#'
#' @return A data.frame is returned
#' @export
#'
#' @examples
#' my.ss.ng.int.req <- return.ss.ng.int.req()
#' head(my.ss.ng.int.req)
return.ss.ng.int.req <-   function(mu.0.t = 0, n.0.t = .0001, alpha.0.t = 0.25, beta.0.t = 1,
                              xbar.t=seq(-5,5,.1), s.t = 2, interim.n.t = c(5, 10, 15, 20, 25, 30, 35),
                              final.n.t = 40,
                              Delta.lrv = 1.25, Delta.tv = 1.75,
                              tau.tv = .1, tau.lrv = .8, tau.ng = .65,
                              xbar_ng = NULL, xbar_go=NULL,
                              go.thresh=0.8, ng.thresh=0.8){

  if(is.null(xbar_ng) | is.null(xbar_go)){
    results <- get.ss.ng.studyend.GNG(mu.0.t = mu.0.t, alpha.0.t=alpha.0.t, beta.0.t = beta.0.t, n.0.t = n.0.t,
                                      xbar.t = xbar.t, s.t = s.t, n.t = final.n.t,
                                      Delta.lrv = Delta.lrv, Delta.tv = Delta.tv,
                                      tau.tv=tau.tv, tau.lrv=tau.lrv, tau.ng=tau.ng)
    xbar_go <- ifelse(nrow(results$result.go) == 0, Inf, results$result.go$xbar)
    xbar_ng <- ifelse(nrow(results$result.ng) == 0, 0,  results$result.ng$xbar)
  }

  my.params <- get.ng.post(mu.0 = mu.0.t, n.0 = n.0.t, alpha.0 = alpha.0.t, beta.0 = beta.0.t,
                           xbar = xbar.t, s = s.t, n = interim.n.t) %>%
    rename(interim.n.t = n) %>%
    mutate(xbar_ng=xbar_ng, xbar_go=xbar_go,
           complement.n.t = final.n.t - interim.n.t) %>%
    mutate(
      t.go = xbar_go*(interim.n.t+complement.n.t)/complement.n.t - interim.n.t/complement.n.t*xbar.t,
      t.ng = xbar_ng*(interim.n.t+complement.n.t)/complement.n.t - interim.n.t/complement.n.t*xbar.t,
      Go = 1 - pt_ls(x = t.go, mu = mu.n, sigma = beta.n*(n.0.t+interim.n.t+complement.n.t)/((n.0.t+interim.n.t)*alpha.n), df=2*alpha.n),
      NoGo =   pt_ls(x = t.ng, mu = mu.n, sigma = beta.n*(n.0.t+interim.n.t+complement.n.t)/((n.0.t+interim.n.t)*alpha.n), df=2*alpha.n),
      decision=case_when(Go > go.thresh ~ "Go",
                         NoGo > ng.thresh ~ "No-Go",
                         TRUE ~ "Consider")
    )
  return(my.params)
}