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Item fit statistics from the power-divergence family

Source: R/itemfitPD.R
itemfitPD.Rd

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
)

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.

Value

an object of class itemfitPD consisting of several elements including:

X2

Chi square statistics, adjusted and unadjusted p values for each item

G2

G square statistics, adjusted and unadjusted p values for each item

PD

PD statistics, adjusted and unadjusted p values for each item

time

time used for the computation

References

Najera, P., Ma, W., Sorrel, M. A. and Abad, F. J. (2025). Assessing Item-Level Fit for the Sequential G-DINA Model.Behaviormetrika.

Author

Pablo Najera Universidad Pontificia Comillas pnajera@comillas.edu

Wenchao Ma University of Minnesota wma@umn.edu

Examples

if (FALSE) { # \dontrun{
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
} # }