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A C D E F G I L M N P Q R S T W Y
| sirt-package | Supplementary Item Response Theory Models |
| automatic.recode | Automatic Method of Finding Keys in a Dataset with Raw Item Responses |
| ccov.np | Nonparametric Estimation of Conditional Covariances of Item Pairs |
| class.accuracy.rasch | Classification Accuracy in the Rasch Model |
| colCumsums.sirt | Some Matrix Functions |
| conf.detect | Confirmatory DETECT Analysis |
| data.activity.itempars | Item Parameters Cultural Activities |
| data.big5 | Dataset Big 5 from 'qgraph' Package |
| data.big5.qgraph | Dataset Big 5 from 'qgraph' Package |
| data.ess2005 | Dataset European Social Survey 2005 |
| data.inv4gr | Dataset for Invariance Testing with 4 Groups |
| data.long | Longitudinal Dataset |
| data.math | Dataset Mathematics |
| data.mcdonald.act15 | Some Datasets from McDonald's _Test Theory_ Book |
| data.mcdonald.LSAT6 | Some Datasets from McDonald's _Test Theory_ Book |
| data.mcdonald.rape | Some Datasets from McDonald's _Test Theory_ Book |
| data.mixed1 | Dataset with Mixed Dichotomous and Polytomous Item Responses |
| data.ml | Multilevel Datasets |
| data.ml1 | Multilevel Datasets |
| data.ml2 | Multilevel Datasets |
| data.noharm18 | Datasets for NOHARM Analysis |
| data.noharmExC | Datasets for NOHARM Analysis |
| data.pars1.2pl | Item Parameters for Three Studies Obtained by 1PL and 2PL Estimation |
| data.pars1.rasch | Item Parameters for Three Studies Obtained by 1PL and 2PL Estimation |
| data.pirlsmissing | Dataset from PIRLS Study with Missing Responses |
| data.pisaMath | Dataset PISA Mathematics |
| data.pisaPars | Item Parameters from Two PISA Studies |
| data.pisaRead | Dataset PISA Reading |
| data.ratings1 | Rating Dataset 1 |
| data.raw1 | Dataset with Raw Item Responses |
| data.read | Dataset Reading |
| data.reck | Datasets from Reckase' Book _Multidimensional Item Response Theory_ |
| data.reck21 | Datasets from Reckase' Book _Multidimensional Item Response Theory_ |
| data.reck61DAT1 | Datasets from Reckase' Book _Multidimensional Item Response Theory_ |
| data.reck61DAT2 | Datasets from Reckase' Book _Multidimensional Item Response Theory_ |
| data.si01 | Some Example Datasets for the 'sirt' Package |
| data.sirt | Some Example Datasets for the 'sirt' Package |
| data.timss | Dataset TIMSS Mathematics |
| data.timss07.G8.RUS | TIMSS 2007 Grade 8 Mathematics and Science Russia |
| data.wide2long | Converting a Data Frame from Wide Format in a Long Format |
| detect.index | Calculation of the DETECT Index |
| dif.logistic.regression | Differential Item Functioning using Logistic Regression Analysis |
| dif.strata.variance | Stratified DIF Variance |
| dif.variance | DIF Variance |
| dirichlet.mle | Maximum Likelihood Estimation of the Dirichlet Distribution |
| dirichlet.simul | Simulation of a Dirichlet Distributed Vectors |
| eigenvalues.manymatrices | Computation of Eigenvalues of Many Symmetric Matrices |
| eigenvalues.sirt | First Eigenvalues of a Symmetric Matrix |
| equating.rasch | Equating in the Generalized Logistic Rasch Model |
| equating.rasch.jackknife | Jackknife Equating Error in Generalized Logistic Rasch Model |
| expl.detect | Exploratory DETECT Analysis |
| f1d.irt | Functional Unidimensional Item Response Model |
| fit.adisop | Fitting the ISOP and ADISOP Model for Frequency Tables |
| fit.isop | Fitting the ISOP and ADISOP Model for Frequency Tables |
| fuzcluster | Clustering for Continuous Fuzzy Data |
| fuzdiscr | Estimation of a Discrete Distribution for Fuzzy Data (Data in Belief Function Framework) |
| genlogis.moments | Calculation of Probabilities and Moments for the Generalized Logistic Item Response Model |
| gom.em | Discrete (Rasch) Grade of Membership Model |
| gom.jml | Grade of Membership Model (Joint Maximum Likelihood Estimation) |
| greenyang.reliability | Reliability for Dichotomous Item Response Data Using the Method of Green and Yang (2009) |
| invariance.alignment | Alignment Procedure for Linking under Approximate Invariance |
| isop.dich | Fit Unidimensional ISOP and ADISOP Model to Dichotomous and Polytomous Item Responses |
| isop.poly | Fit Unidimensional ISOP and ADISOP Model to Dichotomous and Polytomous Item Responses |
| isop.scoring | Scoring Persons and Items in the ISOP Model |
| latent.regression.em.normal | Latent Regression Model for the Generalized Logistic Item Response Model and the Linear Model for Normal Responses |
| latent.regression.em.raschtype | Latent Regression Model for the Generalized Logistic Item Response Model and the Linear Model for Normal Responses |
| linking.haberman | Linking in the 2PL/Generalized Partial Credit Model |
| lsdm | Least Squares Distance Method of Cognitive Validation |
| marginal.truescore.reliability | True-Score Reliability for Dichotomous Data |
| mcmc.2pno | MCMC Estimation of the Two-Parameter Normal Ogive Item Response Model |
| mcmc.2pno.ml | Random Item Response Model / Multilevel IRT Model |
| mcmc.2pnoh | MCMC Estimation of the Hierarchical IRT Model for Criterion-Referenced Measurement |
| mcmc.3pno.testlet | 3PNO Testlet Model |
| mcmc.list.descriptives | Computation of Descriptive Statistics for a 'mcmc.list' Object |
| mcmclist2coda | Write Coda File from an Object of Class 'mcmc.list' |
| md.pattern.sirt | Response Pattern in a Binary Matrix |
| mle.pcm.group | Maximum Likelihood Estimation of Person or Group Parameters in the Generalized Partial Credit Model |
| modelfit.sirt | Assessing Model Fit and Local Dependence by Comparing Observed and Expected Item Pair Correlations |
| monoreg.colwise | Monotone Regression for Rows or Columns in a Matrix |
| monoreg.rowwise | Monotone Regression for Rows or Columns in a Matrix |
| np.dich | Nonparametric Estimation of Item Response Functions |
| pbivnorm2 | Cumulative Function for the Bivariate Normal Distribution |
| person.parameter.rasch.copula | Person Parameter Estimation of the Rasch Copula Model (Braeken, 2011) |
| personfit.stat | Person Fit Statistics for the Rasch Model |
| pgenlogis | Calculation of Probabilities and Moments for the Generalized Logistic Item Response Model |
| plausible.value.imputation.raschtype | Plausible Value Imputation in Generalized Logistic Item Response Model |
| plot.invariance.alignment | Alignment Procedure for Linking under Approximate Invariance |
| plot.isop | Fit Unidimensional ISOP and ADISOP Model to Dichotomous and Polytomous Item Responses |
| plot.mcmc.sirt | Plot Function for Objects of Class 'mcmc.sirt' |
| plot.np.dich | Plot Method for Object of Class 'np.dich' |
| plot.rasch.mml | Estimation of the Generalized Logistic Item Response Model, Ramsay's Quotient Model and a Nonparametric Item Response Model |
| prmse.subscores.scales | Proportional Reduction of Mean Squared Error (PRMSE) for Subscale Scores |
| prob.guttman | Probabilistic Guttman Model |
| qmc.nodes | Calculation of Quasi Monte Carlo Integration Points |
| R2noharm | Estimation of a NOHARM Analysis from within R |
| R2noharm.EAP | EAP Factor Score Estimation |
| R2noharm.jackknife | Jackknife Estimation of NOHARM Analysis |
| rasch.copula2 | Rasch Copula Model |
| rasch.jml | Joint Maximum Likelihood (JML) Estimation of the Rasch Model |
| rasch.jml.biascorr | Bias Correction of Item Parameters for Joint Maximum Likelihood Estimation in the Rasch model |
| rasch.jml.jackknife1 | Jackknifing the IRT Model Estimated by Joint Maximum Likelihood (JML) |
| rasch.mirtlc | Multidimensional Latent Class 1PL and 2PL Model |
| rasch.mml2 | Estimation of the Generalized Logistic Item Response Model, Ramsay's Quotient Model and a Nonparametric Item Response Model |
| rasch.pairwise | Pairwise Estimation Method of the Rasch Model |
| rasch.pairwise.itemcluster | Pairwise Estimation of the Rasch Model for Locally Dependent Items |
| rasch.pml2 | Pairwise Marginal Likelihood Estimation for the Probit Rasch Model |
| rasch.pml3 | Pairwise Marginal Likelihood Estimation for the Probit Rasch Model |
| rasch.prox | PROX Estimation Method for the Rasch Model |
| rasch.va | Estimation of the Rasch Model with Variational Approximation |
| reliability.nonlinearSEM | Estimation of Reliability for Confirmatory Factor Analyses Based on Dichotomous Data |
| rm.facets | Rater Facets Models with Item/Rater Intercepts and Slopes |
| rm.hrm | Hierachical Rater Model Based on Signal Detection Theory (HRM-SDT) |
| rowCumsums.sirt | Some Matrix Functions |
| rowIntervalIndex.sirt | Some Matrix Functions |
| rowKSmallest.sirt | Some Matrix Functions |
| rowKSmallest2.sirt | Some Matrix Functions |
| rowMaxs.sirt | Some Matrix Functions |
| rowMins.sirt | Some Matrix Functions |
| sim.qm.ramsay | Simulate from Ramsay's Quotient Model |
| sim.rasch.dep | Simulation of the Rasch Model with Locally Dependent Responses |
| sim.raschtype | Simulate from Generalized Logistic Item Response Model |
| sirt | Supplementary Item Response Theory Models |
| smirt | Multidimensional Noncompensatory and Compensatory Item Response Model |
| stratified.cronbach.alpha | Stratified Cronbach's Alpha |
| summary.fuzcluster | Clustering for Continuous Fuzzy Data |
| summary.gom | Discrete (Rasch) Grade of Membership Model |
| summary.invariance.alignment | Alignment Procedure for Linking under Approximate Invariance |
| summary.isop | Fit Unidimensional ISOP and ADISOP Model to Dichotomous and Polytomous Item Responses |
| summary.latent.regression | Latent Regression Model for the Generalized Logistic Item Response Model and the Linear Model for Normal Responses |
| summary.lsdm | Least Squares Distance Method of Cognitive Validation |
| summary.mcmc.sirt | Summary Method for Objects of Class 'mcmc.sirt' |
| summary.prob.guttman | Probabilistic Guttman Model |
| summary.R2noharm | Estimation of a NOHARM Analysis from within R |
| summary.R2noharm.jackknife | Jackknife Estimation of NOHARM Analysis |
| summary.rasch.copula2 | Rasch Copula Model |
| summary.rasch.jml | Joint Maximum Likelihood (JML) Estimation of the Rasch Model |
| summary.rasch.mirtlc | Multidimensional Latent Class 1PL and 2PL Model |
| summary.rasch.mml | Estimation of the Generalized Logistic Item Response Model, Ramsay's Quotient Model and a Nonparametric Item Response Model |
| summary.rasch.pairwise | Pairwise Estimation Method of the Rasch Model |
| summary.rasch.pml | Pairwise Marginal Likelihood Estimation for the Probit Rasch Model |
| summary.rm.facets | Rater Facets Models with Item/Rater Intercepts and Slopes |
| summary.rm.hrm | Hierachical Rater Model Based on Signal Detection Theory (HRM-SDT) |
| summary.smirt | Multidimensional Noncompensatory and Compensatory Item Response Model |
| testlet.yen.q3 | Q_3 Statistic of Yen (1984) for Testlets |
| tetrachoric2 | Tetrachoric Correlation Matrix |
| truescore.irt | Conversion of Trait Scores theta into True Scores tau ( theta ) |
| wle.rasch | Weighted Likelihood Estimation of Person Abilities |
| wle.rasch.jackknife | Standard Error Estimation of WLE by Jackknifing |
| yen.q3 | Estimation of the Q_3 Statistic (Yen, 1984) |