Supplementary Item Response Theory Models
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Documentation for package ‘sirt’ version 4.1-15
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A B C D E F G H I L M N P Q R S T U V W X Y
| sirt-package | Supplementary Item Response Theory Models |
-- A --
| anova.gom | Discrete (Rasch) Grade of Membership Model |
| anova.prob.guttman | Probabilistic Guttman Model |
| anova.rasch.copula2 | Multidimensional IRT Copula Model |
| anova.rasch.copula3 | Multidimensional IRT Copula Model |
| anova.rasch.mirtlc | Multidimensional Latent Class 1PL and 2PL Model |
| anova.rasch.mml | Estimation of the Generalized Logistic Item Response Model, Ramsay's Quotient Model, Nonparametric Item Response Model, Pseudo-Likelihood Estimation and a Missing Data Item Response Model |
| anova.rm.facets | Rater Facets Models with Item/Rater Intercepts and Slopes |
| anova.rm.sdt | Hierarchical Rater Model Based on Signal Detection Theory (HRM-SDT) |
| anova.smirt | Multidimensional Noncompensatory, Compensatory and Partially Compensatory Item Response Model |
| anova.xxirt | User Defined Item Response Model |
| automatic.recode | Automatic Method of Finding Keys in a Dataset with Raw Item Responses |
-- B --
| bounds_parameters | Utility Functions in 'sirt' |
| brm.irf | Functions for the Beta Item Response Model |
| brm.sim | Functions for the Beta Item Response Model |
| btm | Extended Bradley-Terry Model |
| btm_sim | Extended Bradley-Terry Model |
-- C --
| categorize | Categorize and Decategorize Variables in a Data Frame |
| ccov.np | Nonparametric Estimation of Conditional Covariances of Item Pairs |
| cfa_meas_inv | Estimation of a Unidimensional Factor Model under Full and Partial Measurement Invariance |
| class.accuracy.rasch | Classification Accuracy in the Rasch Model |
| coef.rasch.evm.pcm | Estimation of the Partial Credit Model using the Eigenvector Method |
| coef.xxirt | User Defined Item Response Model |
| colCumsums.sirt | Some Matrix Functions |
| conf.detect | Confirmatory DETECT and polyDETECT Analysis |
| confint.xxirt | User Defined Item Response Model |
-- D --
| data.activity.itempars | Item Parameters Cultural Activities |
| data.befki | BEFKI Dataset (Schroeders, Schipolowski, & Wilhelm, 2015) |
| data.befki_resp | BEFKI Dataset (Schroeders, Schipolowski, & Wilhelm, 2015) |
| data.big5 | Dataset Big 5 from 'qgraph' Package |
| data.big5.qgraph | Dataset Big 5 from 'qgraph' Package |
| data.bs | Datasets from Borg and Staufenbiel (2007) |
| data.bs07a | Datasets from Borg and Staufenbiel (2007) |
| data.eid | Examples with Datasets from Eid and Schmidt (2014) |
| data.eid.kap4 | Examples with Datasets from Eid and Schmidt (2014) |
| data.eid.kap5 | Examples with Datasets from Eid and Schmidt (2014) |
| data.eid.kap6 | Examples with Datasets from Eid and Schmidt (2014) |
| data.eid.kap7 | Examples with Datasets from Eid and Schmidt (2014) |
| data.ess2005 | Dataset European Social Survey 2005 |
| data.g308 | C-Test Datasets |
| data.inv4gr | Dataset for Invariance Testing with 4 Groups |
| data.liking.science | Dataset 'Liking For Science' |
| data.long | Longitudinal Dataset |
| data.lsem01 | Datasets for Local Structural Equation Models / Moderated Factor Analysis |
| data.lsem02 | Datasets for Local Structural Equation Models / Moderated Factor Analysis |
| data.lsem03 | Datasets for Local Structural Equation Models / Moderated Factor Analysis |
| 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.pw01 | Datasets for Pairwise Comparisons |
| data.ratings | Rating Datasets |
| data.ratings1 | Rating Datasets |
| data.ratings2 | Rating Datasets |
| data.ratings3 | Rating Datasets |
| 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.reck73C1a | Datasets from Reckase' Book _Multidimensional Item Response Theory_ |
| data.reck73C1b | Datasets from Reckase' Book _Multidimensional Item Response Theory_ |
| data.reck75C2 | Datasets from Reckase' Book _Multidimensional Item Response Theory_ |
| data.reck78ExA | Datasets from Reckase' Book _Multidimensional Item Response Theory_ |
| data.reck79ExB | Datasets from Reckase' Book _Multidimensional Item Response Theory_ |
| data.si01 | Some Example Datasets for the 'sirt' Package |
| data.si02 | Some Example Datasets for the 'sirt' Package |
| data.si03 | Some Example Datasets for the 'sirt' Package |
| data.si04 | Some Example Datasets for the 'sirt' Package |
| data.si05 | Some Example Datasets for the 'sirt' Package |
| data.si06 | Some Example Datasets for the 'sirt' Package |
| data.si07 | Some Example Datasets for the 'sirt' Package |
| data.si08 | Some Example Datasets for the 'sirt' Package |
| data.si09 | Some Example Datasets for the 'sirt' Package |
| data.si10 | 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.trees | Dataset Used in Stoyan, Pommerening and Wuensche (2018) |
| data.wide2long | Converting a Data Frame from Wide Format in a Long Format |
| decategorize | Categorize and Decategorize Variables in a Data Frame |
| detect.index | Calculation of the DETECT and polyDETECT Index |
| dexppow | Fit of a L_q Regression Model |
| dif.logistic.regression | Differential Item Functioning using Logistic Regression Analysis |
| dif.strata.variance | Stratified DIF Variance |
| dif.variance | DIF Variance |
| dimproper | Utility Functions in 'sirt' |
| dinvgamma2 | Inverse Gamma Distribution in Prior Sample Size Parameterization |
| dirichlet.mle | Maximum Likelihood Estimation of the Dirichlet Distribution |
| dirichlet.simul | Simulation of a Dirichlet Distributed Vectors |
| dmlavaan | Comparing Regression Parameters of Different lavaan Models Fitted to the Same Dataset |
-- E --
| eigenvalues.manymatrices | Computation of Eigenvalues of Many Symmetric Matrices |
| 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 |
-- F --
| 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) |
-- G --
| genlogis.moments | Calculation of Probabilities and Moments for the Generalized Logistic Item Response Model |
| ginverse_sym | Utility Functions in 'sirt' |
| 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) |
-- H --
| hard_thresholding | Utility Functions in 'sirt' |
-- I --
| invariance.alignment | Alignment Procedure for Linking under Approximate Invariance |
| invariance_alignment_cfa_config | Alignment Procedure for Linking under Approximate Invariance |
| invariance_alignment_constraints | Alignment Procedure for Linking under Approximate Invariance |
| invariance_alignment_simulate | Alignment Procedure for Linking under Approximate Invariance |
| IRT.expectedCounts.MultipleGroupClass | Some Functions for Wrapping with the 'mirt' Package |
| IRT.expectedCounts.rasch.mml | Estimation of the Generalized Logistic Item Response Model, Ramsay's Quotient Model, Nonparametric Item Response Model, Pseudo-Likelihood Estimation and a Missing Data Item Response Model |
| IRT.expectedCounts.SingleGroupClass | Some Functions for Wrapping with the 'mirt' Package |
| IRT.expectedCounts.xxirt | User Defined Item Response Model |
| IRT.factor.scores.rm.facets | Rater Facets Models with Item/Rater Intercepts and Slopes |
| IRT.factor.scores.rm.sdt | Hierarchical Rater Model Based on Signal Detection Theory (HRM-SDT) |
| IRT.factor.scores.xxirt | User Defined Item Response Model |
| IRT.irfprob.gom | Discrete (Rasch) Grade of Membership Model |
| IRT.irfprob.MultipleGroupClass | Some Functions for Wrapping with the 'mirt' Package |
| IRT.irfprob.prob.guttman | Probabilistic Guttman Model |
| IRT.irfprob.rasch.mirtlc | Multidimensional Latent Class 1PL and 2PL Model |
| IRT.irfprob.rasch.mml | Estimation of the Generalized Logistic Item Response Model, Ramsay's Quotient Model, Nonparametric Item Response Model, Pseudo-Likelihood Estimation and a Missing Data Item Response Model |
| IRT.irfprob.rm.facets | Rater Facets Models with Item/Rater Intercepts and Slopes |
| IRT.irfprob.rm.sdt | Hierarchical Rater Model Based on Signal Detection Theory (HRM-SDT) |
| IRT.irfprob.SingleGroupClass | Some Functions for Wrapping with the 'mirt' Package |
| IRT.irfprob.smirt | Multidimensional Noncompensatory, Compensatory and Partially Compensatory Item Response Model |
| IRT.irfprob.xxirt | User Defined Item Response Model |
| IRT.likelihood.gom | Discrete (Rasch) Grade of Membership Model |
| IRT.likelihood.MultipleGroupClass | Some Functions for Wrapping with the 'mirt' Package |
| IRT.likelihood.prob.guttman | Probabilistic Guttman Model |
| IRT.likelihood.rasch.copula2 | Multidimensional IRT Copula Model |
| IRT.likelihood.rasch.copula3 | Multidimensional IRT Copula Model |
| IRT.likelihood.rasch.mirtlc | Multidimensional Latent Class 1PL and 2PL Model |
| IRT.likelihood.rasch.mml | Estimation of the Generalized Logistic Item Response Model, Ramsay's Quotient Model, Nonparametric Item Response Model, Pseudo-Likelihood Estimation and a Missing Data Item Response Model |
| IRT.likelihood.rm.facets | Rater Facets Models with Item/Rater Intercepts and Slopes |
| IRT.likelihood.rm.sdt | Hierarchical Rater Model Based on Signal Detection Theory (HRM-SDT) |
| IRT.likelihood.SingleGroupClass | Some Functions for Wrapping with the 'mirt' Package |
| IRT.likelihood.smirt | Multidimensional Noncompensatory, Compensatory and Partially Compensatory Item Response Model |
| IRT.likelihood.xxirt | User Defined Item Response Model |
| IRT.mle | Person Parameter Estimation |
| IRT.modelfit.gom | Discrete (Rasch) Grade of Membership Model |
| IRT.modelfit.rasch.mirtlc | Multidimensional Latent Class 1PL and 2PL Model |
| IRT.modelfit.rasch.mml | Estimation of the Generalized Logistic Item Response Model, Ramsay's Quotient Model, Nonparametric Item Response Model, Pseudo-Likelihood Estimation and a Missing Data Item Response Model |
| IRT.modelfit.rm.facets | Rater Facets Models with Item/Rater Intercepts and Slopes |
| IRT.modelfit.rm.sdt | Hierarchical Rater Model Based on Signal Detection Theory (HRM-SDT) |
| IRT.modelfit.sirt | Assessing Model Fit and Local Dependence by Comparing Observed and Expected Item Pair Correlations |
| IRT.modelfit.smirt | Multidimensional Noncompensatory, Compensatory and Partially Compensatory Item Response Model |
| IRT.modelfit.xxirt | User Defined Item Response Model |
| IRT.posterior.gom | Discrete (Rasch) Grade of Membership Model |
| IRT.posterior.MultipleGroupClass | Some Functions for Wrapping with the 'mirt' Package |
| IRT.posterior.prob.guttman | Probabilistic Guttman Model |
| IRT.posterior.rasch.copula2 | Multidimensional IRT Copula Model |
| IRT.posterior.rasch.copula3 | Multidimensional IRT Copula Model |
| IRT.posterior.rasch.mirtlc | Multidimensional Latent Class 1PL and 2PL Model |
| IRT.posterior.rasch.mml | Estimation of the Generalized Logistic Item Response Model, Ramsay's Quotient Model, Nonparametric Item Response Model, Pseudo-Likelihood Estimation and a Missing Data Item Response Model |
| IRT.posterior.rm.facets | Rater Facets Models with Item/Rater Intercepts and Slopes |
| IRT.posterior.rm.sdt | Hierarchical Rater Model Based on Signal Detection Theory (HRM-SDT) |
| IRT.posterior.SingleGroupClass | Some Functions for Wrapping with the 'mirt' Package |
| IRT.posterior.smirt | Multidimensional Noncompensatory, Compensatory and Partially Compensatory Item Response Model |
| IRT.posterior.xxirt | User Defined Item Response Model |
| IRT.se.xxirt | User Defined Item Response Model |
| 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 |
| isop.test | Testing the ISOP Model |
-- L --
| L0_polish | Linking in the 2PL/Generalized Partial Credit 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 |
| lavaan2mirt | Converting a 'lavaan' Model into a 'mirt' Model |
| lc.2raters | Latent Class Model for Two Exchangeable Raters and One Item |
| likelihood.adjustment | Adjustment and Approximation of Individual Likelihood Functions |
| linking.haberman | Linking in the 2PL/Generalized Partial Credit Model |
| linking.haberman.lq | Linking in the 2PL/Generalized Partial Credit Model |
| linking.haebara | Haebara Linking of the 2PL Model for Multiple Studies |
| linking.robust | Robust Linking of Item Intercepts |
| linking_haberman_itempars_convert | Linking in the 2PL/Generalized Partial Credit Model |
| linking_haberman_itempars_prepare | Linking in the 2PL/Generalized Partial Credit Model |
| logLik.gom | Discrete (Rasch) Grade of Membership Model |
| logLik.prob.guttman | Probabilistic Guttman Model |
| logLik.rasch.copula2 | Multidimensional IRT Copula Model |
| logLik.rasch.copula3 | Multidimensional IRT Copula Model |
| logLik.rasch.mirtlc | Multidimensional Latent Class 1PL and 2PL Model |
| logLik.rasch.mml | Estimation of the Generalized Logistic Item Response Model, Ramsay's Quotient Model, Nonparametric Item Response Model, Pseudo-Likelihood Estimation and a Missing Data Item Response Model |
| logLik.rm.facets | Rater Facets Models with Item/Rater Intercepts and Slopes |
| logLik.rm.sdt | Hierarchical Rater Model Based on Signal Detection Theory (HRM-SDT) |
| logLik.smirt | Multidimensional Noncompensatory, Compensatory and Partially Compensatory Item Response Model |
| logLik.xxirt | User Defined Item Response Model |
| lq_fit | Fit of a L_q Regression Model |
| lq_fit_estimate_power | Fit of a L_q Regression Model |
| lsdm | Least Squares Distance Method of Cognitive Validation |
| lsem.bootstrap | Local Structural Equation Models (LSEM) |
| lsem.estimate | Local Structural Equation Models (LSEM) |
| lsem.MGM.stepfunctions | Local Structural Equation Models (LSEM) |
| lsem.permutationTest | Permutation Test for a Local Structural Equation Model |
| lsem.test | Test a Local Structural Equation Model Based on Bootstrap |
| lsem_local_weights | Local Structural Equation Models (LSEM) |
-- M --
| 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' |
| mcmc_coef | Some Methods for Objects of Class 'mcmc.list' |
| mcmc_confint | Some Methods for Objects of Class 'mcmc.list' |
| mcmc_derivedPars | Some Methods for Objects of Class 'mcmc.list' |
| mcmc_plot | Some Methods for Objects of Class 'mcmc.list' |
| mcmc_Rhat | Computation of the Rhat Statistic from a Single MCMC Chain |
| mcmc_summary | Some Methods for Objects of Class 'mcmc.list' |
| mcmc_vcov | Some Methods for Objects of Class 'mcmc.list' |
| mcmc_WaldTest | Some Methods for Objects of Class 'mcmc.list' |
| md.pattern.sirt | Response Pattern in a Binary Matrix |
| mgsem | Estimation of Multiple-Group Structural Equation Models |
| mirt.specify.partable | Specify or modify a Parameter Table in 'mirt' |
| mirt.wrapper | Some Functions for Wrapping with the 'mirt' Package |
| mirt.wrapper.coef | Some Functions for Wrapping with the 'mirt' Package |
| mirt.wrapper.fscores | Some Functions for Wrapping with the 'mirt' Package |
| mirt.wrapper.itemplot | Some Functions for Wrapping with the 'mirt' Package |
| mirt.wrapper.posterior | Some Functions for Wrapping with the 'mirt' Package |
| mirt_summary | Some Functions for Wrapping with the 'mirt' Package |
| mle.pcm.group | Maximum Likelihood Estimation of Person or Group Parameters in the Generalized Partial Credit Model |
| modelfit.cor.poly | Assessing Model Fit and Local Dependence by Comparing Observed and Expected Item Pair Correlations |
| 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 |
| move_variables_df | Utility Functions in 'sirt' |
-- N --
| nedelsky.irf | Functions for the Nedelsky Model |
| nedelsky.latresp | Functions for the Nedelsky Model |
| nedelsky.sim | Functions for the Nedelsky Model |
| noharm.sirt | NOHARM Model in R |
| np.dich | Nonparametric Estimation of Item Response Functions |
-- P --
| parmsummary_extend | Includes Confidence Interval in Parameter Summary Table |
| pbivnorm2 | Cumulative Function for the Bivariate Normal Distribution |
| pcm.conversion | Conversion of the Parameterization of the Partial Credit Model |
| pcm.fit | Item and Person Fit Statistics for the Partial Credit Model |
| 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.isop | Fit Unidimensional ISOP and ADISOP Model to Dichotomous and Polytomous Item Responses |
| plot.linking.robust | Robust Linking of Item Intercepts |
| plot.lsdm | Least Squares Distance Method of Cognitive Validation |
| plot.lsem | Local Structural Equation Models (LSEM) |
| plot.lsem.permutationTest | Permutation Test for a Local Structural Equation Model |
| 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, Nonparametric Item Response Model, Pseudo-Likelihood Estimation and a Missing Data Item Response Model |
| plot.rm.sdt | Hierarchical Rater Model Based on Signal Detection Theory (HRM-SDT) |
| polychoric2 | Polychoric Correlation |
| pow | Utility Functions in 'sirt' |
| predict.btm | Extended Bradley-Terry Model |
| predict_scale_group_means | Scaling of Group Means and Standard Deviations |
| print.xxirt | User Defined Item Response Model |
| print_digits | Utility Functions in 'sirt' |
| prior_model_parse | Parsing a Prior Model |
| prmse.subscores.scales | Proportional Reduction of Mean Squared Error (PRMSE) for Subscale Scores |
| prob.guttman | Probabilistic Guttman Model |
-- Q --
| Q3 | Estimation of the Q_3 Statistic (Yen, 1984) |
| Q3.testlet | Q_3 Statistic of Yen (1984) for Testlets |
| qmc.nodes | Calculation of Quasi Monte Carlo Integration Points |
-- R --
| R2conquest | Running ConQuest From Within R |
| R2noharm | Estimation of a NOHARM Analysis from within R |
| R2noharm.EAP | EAP Factor Score Estimation |
| R2noharm.jackknife | Jackknife Estimation of NOHARM Analysis |
| rasch.conquest | Defunct 'sirt' Functions |
| rasch.copula2 | Multidimensional IRT Copula Model |
| rasch.copula3 | Multidimensional IRT Copula Model |
| rasch.evm.pcm | Estimation of the Partial Credit Model using the Eigenvector Method |
| 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, Nonparametric Item Response Model, Pseudo-Likelihood Estimation and a Missing Data 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 | Defunct 'sirt' Functions |
| 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 |
| read.multidimpv | Running ConQuest From Within R |
| read.pimap | Running ConQuest From Within R |
| read.pv | Running ConQuest From Within R |
| read.show | Running ConQuest From Within R |
| read.show.regression | Running ConQuest From Within R |
| read.show.term | Running ConQuest From Within R |
| reliability.nonlinearSEM | Estimation of Reliability for Confirmatory Factor Analyses Based on Dichotomous Data |
| resp_groupwise | Creates Group-Wise Item Response Dataset |
| rexppow | Fit of a L_q Regression Model |
| rinvgamma2 | Inverse Gamma Distribution in Prior Sample Size Parameterization |
| rm.facets | Rater Facets Models with Item/Rater Intercepts and Slopes |
| rm.sdt | Hierarchical Rater Model Based on Signal Detection Theory (HRM-SDT) |
| rmvn | Simulation of a Multivariate Normal Distribution with Exact Moments |
| rm_proc_data | Rater Facets Models with Item/Rater Intercepts and Slopes |
| 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 |
| ruvn | Simulation of a Multivariate Normal Distribution with Exact Moments |
-- S --
| scale_group_means | Scaling of Group Means and Standard Deviations |
| sia.sirt | Statistical Implicative Analysis (SIA) |
| 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 |
| sirt-defunct | Defunct 'sirt' Functions |
| sirt-utilities | Utility Functions in 'sirt' |
| sirt_abs_smooth | Utility Functions in 'sirt' |
| sirt_antifisherz | Utility Functions in 'sirt' |
| sirt_attach_list_elements | Utility Functions in 'sirt' |
| sirt_colMaxs | Utility Functions in 'sirt' |
| sirt_colMeans | Utility Functions in 'sirt' |
| sirt_colMedians | Utility Functions in 'sirt' |
| sirt_colMins | Utility Functions in 'sirt' |
| sirt_colSDs | Utility Functions in 'sirt' |
| sirt_dnorm_discrete | Utility Functions in 'sirt' |
| sirt_eigenvalues | First Eigenvalues of a Symmetric Matrix |
| sirt_fisherz | Utility Functions in 'sirt' |
| sirt_matrix2 | Utility Functions in 'sirt' |
| sirt_optimizer | Utility Functions in 'sirt' |
| sirt_permutations | Utility Functions in 'sirt' |
| sirt_rbind_fill | Utility Functions in 'sirt' |
| sirt_rcpp_discrete_inverse | Utility Functions in 'sirt' |
| sirt_rcpp_polychoric2 | Polychoric Correlation |
| sirt_summary_print_call | Utility Functions in 'sirt' |
| sirt_summary_print_objects | Utility Functions in 'sirt' |
| sirt_summary_print_package | Utility Functions in 'sirt' |
| sirt_summary_print_package_rsession | Utility Functions in 'sirt' |
| sirt_summary_print_rsession | Utility Functions in 'sirt' |
| sirt_sum_norm | Utility Functions in 'sirt' |
| smirt | Multidimensional Noncompensatory, Compensatory and Partially Compensatory Item Response Model |
| soft_thresholding | Utility Functions in 'sirt' |
| stratified.cronbach.alpha | Stratified Cronbach's Alpha |
| summary.btm | Extended Bradley-Terry Model |
| summary.conf.detect | Confirmatory DETECT and polyDETECT Analysis |
| 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.invariance_alignment_constraints | Alignment Procedure for Linking under Approximate Invariance |
| summary.IRT.modelfit.gom | Discrete (Rasch) Grade of Membership Model |
| summary.IRT.modelfit.rasch.mirtlc | Multidimensional Latent Class 1PL and 2PL Model |
| summary.IRT.modelfit.rasch.mml | Estimation of the Generalized Logistic Item Response Model, Ramsay's Quotient Model, Nonparametric Item Response Model, Pseudo-Likelihood Estimation and a Missing Data Item Response Model |
| summary.IRT.modelfit.rm.facets | Rater Facets Models with Item/Rater Intercepts and Slopes |
| summary.IRT.modelfit.rm.sdt | Hierarchical Rater Model Based on Signal Detection Theory (HRM-SDT) |
| summary.IRT.modelfit.smirt | Multidimensional Noncompensatory, Compensatory and Partially Compensatory Item Response Model |
| summary.IRT.modelfit.xxirt | User Defined Item Response Model |
| summary.isop | Fit Unidimensional ISOP and ADISOP Model to Dichotomous and Polytomous Item Responses |
| summary.isop.test | Testing the ISOP Model |
| summary.latent.regression | Latent Regression Model for the Generalized Logistic Item Response Model and the Linear Model for Normal Responses |
| summary.lc.2raters | Latent Class Model for Two Exchangeable Raters and One Item |
| summary.linking.haberman | Linking in the 2PL/Generalized Partial Credit Model |
| summary.linking.haberman.lq | Linking in the 2PL/Generalized Partial Credit Model |
| summary.linking.haebara | Haebara Linking of the 2PL Model for Multiple Studies |
| summary.linking.robust | Robust Linking of Item Intercepts |
| summary.lsdm | Least Squares Distance Method of Cognitive Validation |
| summary.lsem | Local Structural Equation Models (LSEM) |
| summary.lsem.permutationTest | Permutation Test for a Local Structural Equation Model |
| summary.mcmc.sirt | Summary Method for Objects of Class 'mcmc.sirt' |
| summary.mcmc_WaldTest | Some Methods for Objects of Class 'mcmc.list' |
| summary.noharm.sirt | NOHARM Model in R |
| summary.prob.guttman | Probabilistic Guttman Model |
| summary.R2conquest | Running ConQuest From Within R |
| summary.R2noharm | Estimation of a NOHARM Analysis from within R |
| summary.R2noharm.jackknife | Jackknife Estimation of NOHARM Analysis |
| summary.rasch.copula2 | Multidimensional IRT Copula Model |
| summary.rasch.copula3 | Multidimensional IRT Copula Model |
| summary.rasch.evm.pcm | Estimation of the Partial Credit Model using the Eigenvector Method |
| 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, Nonparametric Item Response Model, Pseudo-Likelihood Estimation and a Missing Data 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.sdt | Hierarchical Rater Model Based on Signal Detection Theory (HRM-SDT) |
| summary.smirt | Multidimensional Noncompensatory, Compensatory and Partially Compensatory Item Response Model |
| summary.xxirt | User Defined Item Response Model |
-- T --
| tam2mirt | Converting a fitted 'TAM' Object into a 'mirt' Object |
| testlet.marginalized | Marginal Item Parameters from a Testlet (Bifactor) Model |
| testlet.yen.q3 | Defunct 'sirt' Functions |
| tetrachoric2 | Tetrachoric Correlation Matrix |
| tracemat | Utility Functions in 'sirt' |
| truescore.irt | Conversion of Trait Scores theta into True Scores tau ( theta ) |
-- U --
| unidim.test.csn | Test for Unidimensionality of CSN |
-- V --
| vcov.rasch.evm.pcm | Estimation of the Partial Credit Model using the Eigenvector Method |
| vcov.xxirt | User Defined Item Response Model |
-- W --
| wle.rasch | Weighted Likelihood Estimation of Person Abilities |
| wle.rasch.jackknife | Standard Error Estimation of WLE by Jackknifing |
-- X --
| xxirt | User Defined Item Response Model |
| xxirt_createDiscItem | Create Item Response Functions and Item Parameter Table |
| xxirt_createParTable | Create Item Response Functions and Item Parameter Table |
| xxirt_createThetaDistribution | Creates a User Defined Theta Distribution |
| xxirt_hessian | User Defined Item Response Model |
| xxirt_modifyParTable | Create Item Response Functions and Item Parameter Table |
-- Y --
| yen.q3 | Defunct 'sirt' Functions |