difNLR (version 1.3.7)

fitted.difNLR: Fitted values and residuals for an object of "difNLR" class.

Description

S3 methods for extracting fitted values and residuals for an object of "difNLR" class.

Usage

# S3 method for difNLR
fitted(object, item = "all", ...)
# S3 method for difNLR
residuals(object, item = "all", ...)

Arguments

object

an object of "difNLR" class.

item

numeric or character: either character "all" to apply for all converged items (default), or a vector of item names (column names of Data), or item identifiers (integers specifying the column number).

...

other generic parameters for S3 methods.

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. fitted for generic function extracting fitted values. residuals for generic function extracting residuals.

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"))

# Fitted values
fitted(x)
fitted(x, item = 1)

# Residuals
residuals(x)
residuals(x, item = 1)
# }