predict.difNLR() was fixed.startNLR()
was fixed."em" and "plf" were added for the
method argument in the estimNLR() function to
estimate item parameters with either the EM algorithm or algorithm based
on parametric link function (PLF). “plf” is now default option. This is
also the default option for the NLR() function.parameterization argument of the
formulaNLR() and startNLR() function were
updated (renamed).constraints were added into the
startNLR() function."likelihood" option for maximum likelihood estimation
in the estimNLR() function was renamed to
"mle".estimNLR() function were extended
and improved.THIS IS A CRAN VERSION
plot.ddfMLR() now correctly plots ordinal data.test = "W" was fixed for the
difNLR() and NLR() functions.difNLR() and
NLR() functions.startNLR now handles missing values. Returns error when
not enough complete observations are provided.ggplot2 plotting methods were updated to
follow changes in the ggplot2 package.ggplot2 plotting
methods were updated.ggplot2 v.3.4.0 is now imported.difORD() and ORD()
functions were updated. Now using the Anxiety dataset from
the ShinyItemAnalysis package.class handling was updated.It includes versions 1.3.7-1 - 1.3.7-3
parameterization = "logistic" was fixed in
formulaNLR() function.difNLR(), NLR(), and
estimNLR() functions.coef.difNLR(), coef.difORD(), and
coef.ddfMLR() methods now include delta method for IRT and
logistic parameterizations.coef.difNLR(), coef.difORD(), and
coef.ddfMLR() methods now include calculation of confidence
intervals.estimNLR() function is now unified via
print() method.predicted.difORD() to compute
predicted values for difORD object was implemented.plot.difNLR() fixed.THIS IS A CRAN VERSION
Data in
ddfMLR() to fix bug when plotting.method = "nls" was implemented into the vcov()
method for the output of the estimNLR() function.difNLR()
function.method = "nls" was implemented into the
difNLR() function via an argument
sandwich = TRUE.THIS IS A CRAN VERSION
difNLR() function was fixed.THIS IS A CRAN VERSION
difNLR() was fixed.difNLR() for non-converged items
including naming of parameters was fixed (Reported by Jan Netik).NLR(), function gives warning and NA values
for covariance matrix and vector of standard errors are returned.predict.difNLR()
method.difNLR().plot.difNLR(),
plot.difORD() and plot.ddfMLR() were removed.
Change of colours/linetypes/shapes/title can be managed using standard
ggplot2 syntax.plot.difNLR() now offers possibility to turn off
drawing of empirical probabilities using argument
draw.empirical = FALSE.plot.difNLR() now offers possibility to plot confidence
intervals for predicted values as offered in
predict.difNLR() using argument
draw.CI = TRUE.startNLR() were improved
for score as matching criterion using argument
match.plot.difNLR(), plot.difORD()
and plot.ddfMLR() were unified.plot.difORD() and plot.ddfMLR()
were changed to blind-color friendly palettes.THIS IS A CRAN VERSION
plot.difNLR() was fixed.THIS IS A CRAN VERSION
It includes versions 1.3.0-1 - 1.3.0-6 and following changes:
plot.difNLR() now correctly uses matching
criterion when item purification is applied.markdown.MLR() function now returns correct value of
log-likelihood for alternative model.NLR() function was
set to "all" instead of "both".Data in difNLR() function can be
also a vector now.MLR() was fixed for binary data and IRT
parametrization.print.difORD() method.plot.ddfMLR() was fixed for binary data.ddfORD() was renamed to
difORD().genNLR() with an option
itemtype = "nominal" returns nominal items as factors with
levels presented by capital letters.plot.ddfMLR() was updated to show P(Y =
option) instead of option alone.NLR() estimation.item for S3 methods of difNLR
class can be now name of the column in Data.plot.ddfMLR() and plot.ddfORD()
were updated.difNLR() function
was set to "all" instead of "both".styler was used to improve formatting of the
code.ShinyItemAnalysis was added into Suggests.estimNLR() was improved.plot.ddfORD() is now correctly
displayed.THIS IS A CRAN VERSION
It includes versions 1.2.3 - 1.2.8-4 and following changes:
print.difNLR()print.ddfORD() and print.ddfMLR().plot.ddfORD() uses anchor
items.plot.ddfORD() now works when Data is factor.genNLR() now generates ordinal data using adjacent
category logit model with argument
itemtype = "ordinal".plot.ddfORD() now works when items have different
scales.anchor is now used for calculation of matching
criterion in function ORD().ddfORD().logLik.ddfMLR() now works properly.plot.ddfORD() and plot.ddfMLR().plot.difNLR() can
be changed with group.name argument.difNLR(), ddfMLR(),
ddfORD(), MLR(), and ORD()
functions were updated.ddfMLR() function
with argument parametrization. SE calculated with delta
method.plot.ddfMLR() can
be changed with group.name argument.ddfORD() function was renamed. Now
ddfORD().ddfORD() function
with argument parametrization. SE calculated with delta
method.plot.ddfORD() can
be changed with group.name argument.ddfORD() was updated.ddfORD() was added.item in S3 methods for
difNLR(), ddfMLR(), and ddfORD()
was fixed.plot() outputs for difNLR(),
ddfMLR(), and ddfORD() functions were
unified.plot() for ddfORD() was
implemented.AIC(), BIC(),
logLik(), coef() for ddfORD()
were implemented.AIC(), BIC(),
logLik(), residuals() for
difNLR() and ddfMLR() objects now handle
column names as item argument.coef() for difNLR and
ddfMLR objects were updated. Their now includes arguments
SE (logical) to print standard errors and
simplify (logical) whether list of estimates should be
simplified into a matrix.ddfORD() and ORD() for DDF
detection for ordinal data with adjacent and cumulative logistic
regression models were added. Output is displayed via S3 method
print.ddfORD()ddfMLR(), MLR(), and
difNLR() were updated.plot.ddfMLR() now handles also binary data.ddfMLR() returns consistently
"No DDF item detected" when no DDF item was detected.plot.ddfMLR() was improved for
displaying more smooth curves.THIS IS A CRAN VERSION
It includes versions 1.2.1-1 - 1.2.1-3
AIC(), BIC(),
logLik() of ddfMLR() are now item
specific.difNLR()
NLR()
initboot = FALSE now works properly.difNLR():
ddfMLR():
THIS IS A CRAN VERSION
It includes versions 1.2.0-1 - 1.2.0-7
start in difNLR() function is now
item-specific. The input is correctly checked.difNLR() and NLR() functions.constraints in difNLR() function
is now item-specific.print() method for
difNLR class.difNLR class are now properly described,
especially, plot.difNLR() and
predict.difNLR().difNLR() documentation was improved.difNLR can now properly handle
items with convergence issues.NLR() now detects DIF correctly with F test.print(), plot(),fitted(),
predict(), logLik(), AIC(),
BIC() and residuals() for difNLR
class now handles item specific arguments (model,
type and constraints).residuals for difNLR class now uses
argument item.difNLR was fixed and improved.NLR().NLR().difNLR class can now handle convergence
issues.difNLR-package was updated.plot() and residuals() for
difNLR was slightly improved.logLik() for difNLR now returns list of
logLik class values.startNLR() now handles item-specific arguments
(model and parameterization). Its output is
now in the form of list. It can be simplified with argument
simplify into table when all parameterizations are the
same.NLR() now handles item-specific arguments
(model, type and
constraints).difNLR() now handles item-specific arguments
(model, type and
constraints).estimNLR() in
NLR() are now properly named.formulaNLR() was fixed.formulaNLR() and
estimNLR() were improved.genNLR() can now also generate nominal data
based on model specified in ddfMLR().parameters in genNLR() is no
longer applicable.a, b, c,
d were added into genNLR() as parameters -
discrimination, difficulty, guessing, inattentiongenNLR() can now also generate different
underlying distributions for reference and focal group with arguments
mu and sigma.estimNLR() to estimate parameters of NLR
models was added. This function uses non-linear least squares or maximum
likelihood method.NLR() now uses estimNLR() for
estimation of models parameters.difNLR() can now estimate models parameters
with also maximum likelihood method.estimNLR() function. This option is not fully
functional.plot() for ddfMLR class in matching
criterion was fixed.NLR() was fixed. User-specified starting values
are now available.startNLR() was fixed. Function runs even if
there are not unique cuts for total scores/match.estimNLR() was
fixed.NLR() was done.NLR() function was fixed.match argument in difNLR() function
was fixed.Data in difNLR()
function was fixed.startNLR() function was improved.ddfMLR() and MLR() can now
handle also total score or other user-specified matching criterion.plot() for class ddfMLR can
also handle total score or other user-specified matching criterion.checkInterval() was added.difNLR() and ddfMLR().residuals.difNLR() was added.AIC() and BIC() for
difNLR class were updated.plot(), fitted() and
predict() for difNLR class can now handle also
other matching criteria than zscore.THIS IS A CRAN VERSION
startNLR() function for missing values was
fixed.difNLR() and
ddfMLR() functions was mildly updated and unified.THIS IS A CRAN VERSION
plot.difNLR() was fixed.constraints arguments in
NLR() and formulaNLR() functions were set to
NULL.NLR() function
by startNLR() function.difNLR() function can handle Data with one
column.startNLR() now works when match argument
is set.formulaNLR()
function.NLR() function.startNLR() was mildly updated.ddfMLR()
function.ddfMLR()
function.MLR() function.logLik.ddfMLR() function was fixed.difNLR() was updated.difNLR()
function.difNLR()
function.NLR() function.difMedical, difMedicaltest, and
difMedicalkey were renamed. Now they are
MSATB, MSATBtest, and MSATBkey.
from Medical School Admission Test in Biology.formulaNLR() was implemented. Function
returns formula for NLR model for 11 predefined models and 4 predefined
DIF types to test. Model and DIF type can be also specified with
constraints on parameters a, b, c and d.NLR() now handles 11 predefined models and 4
predefined DIF types to test. Model and DIF type can be also specified
with constraints on parameters a, b, c and d.startNLR() was edited to return starting
parameters with different parameterization. It was also mildly changed
to correspond to new version of NLR() function.difNLR() can now handle also total score or
other user-specified matching score.constrNLR() is no longer part of the
difNLR package.difNLR() and
ddfMLR() functions.difNLR()
function.msm package is now used for delta method in
difNLR() function.THIS IS A CRAN VERSION
plot.ddfMLR() for non-uniform DDF was
fixed.THIS IS A CRAN VERSION
difNLR()
function was fixed.GMAT and GMATtest were extended
by criterion variable which is intended to be predicted by
test.coef, logLik, AIC and
BIC S3 methods were added for class
ddfMLR.plot.ddfMLR() and plot.difNLR()
were slightly improved.difNLR() and
ddfMLR() functions.THIS IS A CRAN VERSION
ddfMLR() to detect Differential Distractor
Functioning (DDF) with Multinomial Log-linear Regression (MLR) model. S3
methods for class ddfMLR also added - print
and plot.MLR() to calculate likelihood ratio
statistic for detecting DDF with MLR model.difNLR() function can handle 6 generalized logistic
regression models with option model.startNLR(), genNLR() ans S3
methods for class difNLR were changed according
difNLR() function. S3 method coef was
created.NLR() and constrNLR() can
now calculates DIF detection statistics and specify constraints for
generalized logistic regression model.difNLR() was edited to response to
difR package and its DIF detection functions.genNLR() was changed to generate dataset from
generalized logistic regression model with 8 parameters.AIC(), BIC(), and logLik() S3
methods added to difNLR().THIS IS A CRAN VERSION
plot for class difNLR was
updated.test in difNLR() function
was added. Possible choices are now F for F-test and
LR for likelihood ratio test.alpha was added into
difNLR() function with default option 0.05.GMAT data, its
unscored version GMATtest and its key GMATkey.
Scored difMedical data set, its unscored version
difMedicaltest and key difMedicalkey.genNLR() was added to generate scored
(binary) data with model by difNLR.