# Calculates DTF index for a set of items with given item parameters of focal and reference groups. ```r Dtf( cdif = NULL, itemParameters = NULL, irtModel = "2pl", focalAbilities = NULL, focalDistribution = "norm", subdivisions = 5000, logistic = TRUE, focalDistrExtra = list(mean = 0, sd = 1) ) ``` ## Arguments - `cdif`: A numeric vector of CDIF values for the test items. If NULL it is calculated using itemParameters and the other arguments. - `itemParameters`: A list containing "focal" and "reference" item parameters. Item parameters are assumed to be on the same scale. Only used if cdif is NULL. Item parameters for each group should me a matrix with nrow equal to the number of items. - `irtModel`: A string stating the irtModel to be used. Should be one of "1pl", "2pl", "3pl", "grm" or "pcm". Only used if cdif is NULL. - `focalAbilities`: If NULL, CDIF is calculated by numerical integration of focal distribution. If not NULL, it must be a numerical vector containing the abilities for the individuals in the focal group. Only used if cdif is NULL. - `focalDistribution`: A string stating the distribution name to be used for integrating. Only used if focalAbilities and cdif are NULL. - `subdivisions`: A numeric value indicating the number of subdivisions for numerical integration. Only used if focalAbilities and cdif are NULL. - `logistic`: A logical value stating if the IRT model will use the logistic or the normal metric. Defaults to using the logistic metric by fixing the D constant to 1. If FALSE the constant is set to 1.702 so that the normal metric is used. Only used if cdif is NULL. - `focalDistrExtra`: Extra parameters for the focal group distribution function if needed. ## Returns dtf Numeric vector with the CDIF index value for each item. ## Examples ```r # # Not run # # # # data(dichotomousItemParameters) # # # # threePlParameters <- dichotomousItemParameters # # isNot3Pl <- ((dichotomousItemParameters[['focal']][, 3] == 0) | # # (dichotomousItemParameters[['reference']][, 3] == 0)) # # # # threePlParameters[['focal']] <- threePlParameters[['focal']][!isNot3Pl, ] # # threePlParameters[['reference']] <- threePlParameters[['reference']][!isNot3Pl, ] # # threePlParameters[['focal']][, 3] <- threePlParameters[['focal']][, 3] + 0.1 # # threePlParameters[['reference']][, 3] <- threePlParameters[['reference']][, 3] + 0.1 # # threePlParameters[['focal']][, 2] <- threePlParameters[['focal']][, 2] + 1.5 # # threePlParameters[['reference']][, 2] <- threePlParameters[['reference']][, 2] + 1.5 # # threePlParameters[['focal']] <- threePlParameters[['focal']][-c(12, 16, 28), ] # # threePlParameters[['reference']] <- threePlParameters[['reference']][-c(12, 16, 28), ] # # # # threePlCdif <- Cdif(itemParameters = threePlParameters, irtModel = '3pl', # # focalAbilities = NULL, focalDistribution = "norm", # # subdivisions = 5000, logistic = TRUE) # # threePlDtf <- Dtf(cdif = threePlCdif) ``` ## References Raju, N. S., van der Linden, W. J., & Fleer, P. F. (1995). IRT-based internal measures of differential functioning of items and tests. Applied Psychological Measurement, 19, 353--368. doi:10.1177/014662169501900405 ## Author(s) Victor H. Cervantes

Dtf function