#' Ln of Diagnosticity Ratio
#'
#' Computes ln of diagnosticity ratio: ln(d)
#' @param linedf A dataframe of parameters for computing diagnosticity ratio
#' @details \strong{To get linedf, use the diag_param helper function}
#'
#' \emph{diag_param} returns a dataframe containing the following:
#'
#' \itemize{
#' \item \emph{n11}: Number of mock witnesses who identified the suspect in the target
#' present condition
#'
#' \item \emph{n21}: Number of mock witnesses who did not identify the suspect in the
#' target present condition
#'
#' \item \emph{n12}: Number of mock witnesses who identified the suspect in the target
#' absent condition
#'
#' \item \emph{n13}: Number of mock witnesses who did not identify the suspect in the
#' target absent condition
#' }
#'@references Malpass, R. S. (1981). Effective size and defendant bias in
#' eyewitness identification lineups. \emph{Law and Human Behavior, 5}(4), 299-309.
#'
#' Malpass, R. S., Tredoux, C., & McQuiston-Surrett, D. (2007). Lineup
#' construction and lineup fairness. In R. Lindsay, D. F. Ross, J. D. Read,
#' & M. P. Toglia (Eds.), \emph{Handbook of Eyewitness Psychology, Vol. 2: Memory for
#' people} (pp. 155-178). Mahwah, NJ: Lawrence Erlbaum Associates.
#'
#' Tredoux, C. G. (1998). Statistical inference on measures of lineup fairness.
#' \emph{Law and Human Behavior, 22}(2), 217-237.
#'
#' Tredoux, C. (1999). Statistical considerations when determining measures of
#' lineup size and lineup bias. \emph{Applied Cognitive Psychology, 13}, S9-S26.
#'
#' Wells, G. L.,Leippe, M. R., & Ostrom, T. M. (1979). Guidelines for
#' empirically assessing the fairness of a lineup. \emph{Law and Human Behavior,
#' 3}(4), 285-293.
#'@examples
#'#Target present data:
#'A <- round(runif(100,1,6))
#'B <- round(runif(70,1,5))
#'C <- round(runif(20,1,4))
#'lineup_pres_list <- list(A, B, C)
#'rm(A, B, C)
#'
#'
#'#Target absent data:
#'A <- round(runif(100,1,6))
#'B <- round(runif(70,1,5))
#'C <- round(runif(20,1,4))
#'lineup_abs_list <- list(A, B, C)
#'rm(A, B, C)
#'
#'#Pos list
#'lineup1_pos <- c(1, 2, 3, 4, 5, 6)
#'lineup2_pos <- c(1, 2, 3, 4, 5)
#'lineup3_pos <- c(1, 2, 3, 4)
#'pos_list <- list(lineup1_pos, lineup2_pos, lineup3_pos)
#'rm(lineup1_pos, lineup2_pos, lineup3_pos)
#'
#'#Nominal size:
#'k <- c(6, 5, 4)
#'
#'#Use diag param helper function to get data (n11, n21, n12, n22):
#'linedf <- diag_param(lineup_pres_list, lineup_abs_list, pos_list, k)
#'
#'#Call:
#'lnd <- ln_diag_ratio(linedf)
#'
#'@export
#'
ln_diag_ratio <- function(linedf){
d <- (linedf$n11+0.5/((linedf$n11+linedf$n21)+0.5))/
(linedf$n12+0.5/((linedf$n12+linedf$n22)+0.5))
lnd <- log(d)
lnd <- as.data.frame(lnd)
return(lnd)
}
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