fitted.difNLR | R Documentation |
"difNLR"
class.S3 methods for extracting fitted values and residuals for an object of the
"difNLR"
class.
## S3 method for class 'difNLR'
fitted(object, item = "all", ...)
## S3 method for class 'difNLR'
residuals(object, item = "all", ...)
object |
an object of the |
item |
numeric or character: either character |
... |
other generic parameters for S3 methods. |
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
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, \Sexpr[results=rd]{tools:::Rd_expr_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, \Sexpr[results=rd]{tools:::Rd_expr_doi("10.32614/RJ-2020-014")}.
difNLR
for DIF detection among binary data using the generalized logistic regression model.
fitted
for a generic function extracting fitted values.
residuals
for a generic function extracting residuals.
## 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"))
# fitted values
fitted(x)
fitted(x, item = 1)
fitted(x, item = x$DIFitems)
# residuals
residuals(x)
residuals(x, item = 1)
residuals(x, item = x$DIFitems)
## End(Not run)
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