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 describedm, 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 criterions 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 also added - print and plot.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.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.