difNLR (version 1.3.7)

coef.difNLR: Extract model coefficients from an object of "difNLR" class.

Description

S3 method for extracting model coefficients from an object of "difNLR" class.

Usage

# S3 method for difNLR
coef(object, SE = FALSE, simplify = FALSE, ...)

Arguments

object

an object of "difNLR" class.

SE

logical: should the standard errors of estimated parameters be also returned? (default is FALSE).

simplify

logical: should the estimated parameters be simplified to a matrix? (default is FALSE).

...

other generic parameters for predict() function.

References

Drabinova, A. & Martinkova, P. (2017). Detection of differential item functioning with nonlinear regression: A non-IRT approach accounting for guessing. Journal of Educational Measurement, 54(4), 498--517, 10.1111/jedm.12158.

Hladka, A. & Martinkova, P. (2020). difNLR: Generalized logistic regression models for DIF and DDF detection. The R journal, 12(1), 300--323, 10.32614/RJ-2020-014.

Swaminathan, H. & Rogers, H. J. (1990). Detecting differential item functioning using logistic regression procedures. Journal of Educational Measurement, 27(4), 361--370, 10.1111/j.1745-3984.1990.tb00754.x

See Also

difNLR for DIF detection among binary data using generalized logistic regression model. coef for generic function extracting model coefficients.

Examples

# NOT RUN {
# Loading data based on GMAT
data(GMAT)

Data <- GMAT[, 1:20]
group <- GMAT[, "group"]

# Testing both DIF effects using likelihood-ratio test and
# 3PL model with fixed guessing for groups
(x <- difNLR(Data, group, focal.name = 1, model = "3PLcg"))

# Coefficients
coef(x)
coef(x, SE = TRUE)
coef(x, SE = TRUE, simplify = TRUE)
# }