coef.difNLR {difNLR} | R Documentation |
Extract item parameter estimates from an object of the "difNLR"
class.
Description
S3 method for extracting the item parameter estimates from an object of the "difNLR"
class.
Usage
## S3 method for class 'difNLR'
coef(
object,
item = "all",
SE = FALSE,
simplify = FALSE,
IRTpars = TRUE,
CI = 0.95,
...
)
Arguments
object |
an object of the |
item |
numeric or character: either character |
SE |
logical: should the standard errors of the estimated item parameters
be also returned? (the default is |
simplify |
logical: should the estimated item parameters be simplified to a
matrix? (the default is |
IRTpars |
logical: should the estimated item parameters be returned in he
IRT parameterization? (the default is |
CI |
numeric: a significance level for confidence intervals (CIs) of item
parameter estimates (the default is |
... |
other generic parameters for the |
Author(s)
Adela Hladka (nee Drabinova)
Institute of Computer Science of the Czech Academy of Sciences
hladka@cs.cas.cz
Patricia Martinkova
Institute of Computer Science of the Czech Academy of Sciences
martinkova@cs.cas.cz
Karel Zvara
Faculty of Mathematics and Physics, Charles University
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, doi: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, doi:10.32614/RJ-2020-014.
See Also
difNLR
for DIF detection among binary data using the generalized logistic regression model.
coef
for a generic function for extracting parameter estimates.
Examples
## Not run:
# loading data
data(GMAT)
Data <- GMAT[, 1:20] # items
group <- GMAT[, "group"] # group membership variable
# 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"))
# estimated parameters
coef(x)
# includes standard errors
coef(x, SE = TRUE)
# includes standard errors and simplifies to matrix
coef(x, SE = TRUE, simplify = TRUE)
# intercept-slope parameterization
coef(x, IRTpars = FALSE)
# intercept-slope parameterization, simplifies to matrix, turn off confidence intervals
coef(x, IRTpars = FALSE, simplify = TRUE, CI = 0)
# for DIF items only
coef(x, item = x$DIFitems, IRTpars = FALSE, simplify = TRUE, CI = 0)
## End(Not run)