R/NI.Dorf.calc1.R

In binGroup2: Identification and Estimation using Group Testing

# Start  NI.Dorf.calc1() function
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# Brianna Hitt - 12-06-19
# This function is the same as NI.Dorf(), but no longer finds the 
#   optimal testing configuration. It only calculates operating
#   characteristics for a specific testing configuration.

NI.Dorf.calc1 <- function(p, Se, Sp, group.sz, a, 
                          trace = TRUE, print.time = TRUE, ...) {
  
  start.time <- proc.time()
  
  I <- group.sz
  
  # generate a probability vector for homogeneous population
  p.vec <- rep(x = p[1], times = I)
  order.for.p <- 1:I
  
  # calculate descriptive measures for two-stage hierarchical testing
  save.info <- hierarchical.desc2(p = p.vec[order.for.p], 
                                  se = Se, sp = Sp, I2 = NULL, 
                                  order.p = FALSE)
  
  # extract ET, PSe, PSp and calculate the MAR function
  ET <- save.info$ET
  
  # for non-informative Dorfman (two-stage hierarchical) testing, 
  #   all individuals have the same testing accuracy measures
  check <- check.all.equal(save.info$individual.testerror, 
                           which(colnames(save.info$individual.testerror) == "psp.vec"))
  if (is.null(check)) {
    ind.testerror <- get.unique.index(save.info$individual.testerror[a,], 
                                      which(colnames(save.info$individual.testerror) == "psp.vec"), 
                                      rowlabel = a)[,-1]
  } else {
    ind.testerror <- check[,-1]
  }
  colnames(ind.testerror) <- c("PSe", "PSP", "PPPV", "PNPV", "individuals")
  
  group.testerror <- save.info$group.testerror
  names(group.testerror) <- NULL
  PSe <- group.testerror[1]
  PSp <- group.testerror[2]
  PPPV <- group.testerror[3]
  PNPV <- group.testerror[4]
  
  save.it <- c(p[1], I, ET, ET / I, PSe, PSp, PPPV, PNPV)
  
  # put accuracy measures in a matrix for easier display of results
  acc.ET <- matrix(data = save.it[5:8], nrow = 1, ncol = 4, 
                   dimnames = list(NULL, c("PSe", "PSp", "PPPV", "PNPV")))
  
  # create input accuracy value matrices for output display
  Se.display <- matrix(data = Se, nrow = 1, ncol = 2, 
                       dimnames = list(NULL, "Stage" = 1:2))
  Sp.display <- matrix(data = Sp, nrow = 1, ncol = 2, 
                       dimnames = list(NULL, "Stage" = 1:2))
  
  # print time elapsed, if print.time == TRUE
  if (print.time) {
    time.it(start.time)
  }
  
  list("algorithm" = "Non-informative two-stage hierarchical testing",
       "prob" = p[1], "Se" = Se.display, "Sp" = Sp.display, 
       "Config" = list("Stage1" = save.it[2]), "p.vec" = p.vec, 
       "ET" = save.it[3], "value" = save.it[4], 
       "Accuracy" = list("Individual" = ind.testerror, "Overall" = acc.ET))
}

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