1d:T769,# Diagnosticity ratio weights Function to compute weights of each diagnosticity ratio for k lineup pairs ```r d_weights(linedf) ``` ## Arguments - `linedf`: A dataframe of parameters for computing diagnosticity ratio ## Returns A dataframe with one column containing weights for each pair of lineups for which diagnosticity ratio is being calculated. ## Details In order to obtain a pooled estimate of a set of diagnosticity ratios, we use a weight for each ratio that is equal to the inverse of its variance. To get linedf, use the diag_param helper function **diag_param** returns a dataframe containing the following: * **n11**: Number of mock witnesses who identified the suspect in the target present condition * **n21**: Number of mock witnesses who did not identify the suspect in the target present condition * **n12**: Number of mock witnesses who identified the suspect in the target absent condition * **n13**: Number of mock witnesses who did not identify the suspect in the target absent condition ## Examples ```r #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: wi <- d_weights(linedf) ``` ## References Tredoux, C. G. (1998). Statistical inference on measures of lineup fairness. **Law and Human Behavior, 22**(2), 217-237.

d_weights function