GDINA (version 2.9.12)

itemfitPD: Item fit statistics from the power-divergence family

Description

Calculate item fit statistics from the power-divergence family

Usage

itemfitPD(
  GDINA.obj,
  lambda = 2/3,
  bootstrap = FALSE,
  R = 1000,
  Stone = FALSE,
  init.parm = FALSE,
  p.adjust.method = "holm",
  person.sim = "post",
  cores = 2,
  digits = 4,
  bound = 1e-10,
  seed = 123456
)

Value

an object of class itemfitPD consisting of several elements including:

p

the proportion correct statistics, adjusted and unadjusted p values for each item

r

the transformed correlations, adjusted and unadjusted p values for each item pair

logOR

the log odds ratios, adjusted and unadjusted p values for each item pair

maxitemfit

the maximum proportion correct, transformed correlation, and log-odds ratio for each item with associated item-level adjusted p-values

#' @importFrom foreach

Arguments

GDINA.obj

Object containing a model fitted with the GDINA::GDINA function.

lambda

Numeric; parameter for the power-divergence fit statistic.

bootstrap

Logical; whether parametric bootstrap should be used.

R

Integer; number of replicates in the bootstrap procedure if used.

Stone

Logical; whether Stone indices should be computed (only available if bootstrap = TRUE).

init.parm

Logical; whether the estimated item parameters are used in the estimation of the bootstrap replications.

p.adjust.method

p-values can be adjusted for multiple comparisons at item level. This is conducted using p.adjust function in stats, and therefore all adjustment methods supported by p.adjust can be used, including "holm", "hochberg", "hommel", "bonferroni", "BH" and "BY". See p.adjust for more details. "holm" is the default.

person.sim

Character; how to simulate attribute profiles in the bootstrap replications.

cores

Integer; number of cores for parallelization during bootstrap.

digits

Integer; number of decimal digits to report.

bound

Numeric; minimum possible value for probabilities.

seed

random seed.

Author

Pablo Najera Universidad Pontificia Comillas

Wenchao Ma University of Minnesota

References

Najera, P., Ma, W., Sorrel, M. A. and Abad, F. J. (Under review). Assessing Item-Level Fit for the Sequential G-DINA Model.

Examples

if (FALSE) {
dat <- sim10GDINA$simdat
Q <- sim10GDINA$simQ

mod1 <- GDINA(dat = dat, Q = Q, model = "GDINA")
mod1
PDfit <- itemfitPD(mod1)
PDfit

dat <- sim21seqDINA$simdat
Q <- sim21seqDINA$simQ
sDINA <- GDINA(dat,Q,model="DINA",sequential = TRUE)
PDfit <- itemfitPD(sDINA)
PDfit
PDfit <- itemfitPD(sDINA, bootstrap = TRUE, Stone = TRUE, cores = 10)
PDfit
}