personFit {cdmTools}

Calculate standardized log-likelihood statistic (lZ) for person fit evaluation

Description

This function calculates the standardized log-likelihood statistic (lZ; Cui & Li, 2015; Drasgow et al. 1985) and the proposals for correcting its distribution discussed in Santos et al. (2019).

Usage

personFit(fit, att.est = "MLE", sig.level = 0.05, p.adjust.method = "BH")

Arguments

fit

An object of class RDINA or GDINA (Ma & de la Torre, 2020).

att.est

What attribute estimates are used? The default is "MLE".

sig.level

Scalar numeric. Alpha level for decision. Default is 0.05.

p.adjust.method

Scalar character. Correction method for p-values. Possible values include "holm", "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr", and "none". See p.adjust function from the stats R package for additional details. Default is BH.

Value

personFit returns an object of class personFit, with a list of elements:

stat

Person fit statistics (data.frame).

p

p-values (two-sided test) for the person fit statistics (data.frame).

sigp

Scalar vectors denoting the examinees for which the person fit statitic is significant (p-value) (list).

sigadjp

Scalar vectors denoting the examinees for which the person fit statitic is significant (adjusted p-value) (list).

Author(s)

Miguel A. Sorrel, Universidad Autónoma de Madrid,
Kevin Santos, University of the Philippines,
Pablo Nájera, Universidad Pontificia Comillas

References

Cui, Y., & Li, J. (2015). Evaluating person fit for cognitive diagnostic assessment. Applied Psychological Measurement, 39, 223–238. https://doi.org/10.1177/0146621614557272

Drasgow, F., Levine, M. V., & Williams, E. A. (1985). Appropriateness measurement with polychotomous item response models and standardized indices. British Journal of Mathematical and Statistical Psychology, 38, 67–86. https://psycnet.apa.org/doi/10.1111/j.2044-8317.1985.tb00817.x

Santos, K. C. P., de la Torre, J., & von Davier, M. (2020). Adjusting person fit index for skewness in cognitive diagnosis modeling. Journal of Classification, 37, 399-420. https://doi.org/10.1007/s00357-019-09325-5

Examples

library(GDINA)
dat <- sim10GDINA$simdat[1:20, ]
Q <- sim10GDINA$simQ
fit <- GDINA(dat = dat, Q = Q, model = "GDINA")
res.personFit <- personFit(fit)
res.personFit