Function reference • TAM

All functions
`anova(<tam>)` `logLik(<tam>)` `anova(<tam.mml>)` `logLik(<tam.mml>)` `anova(<tam.mml.3pl>)` `logLik(<tam.mml.3pl>)` `anova(<tamaan>)` `logLik(<tamaan>)` `anova(<tam.latreg>)` `logLik(<tam.latreg>)` `anova(<tam.np>)` `logLik(<tam.np>)`	Likelihood Ratio Test for Model Comparisons and Log-Likelihood Value
`cfa.extract.itempars()`	Extracting Item Parameters from a Fitted `cfa` Object in lavaan
`data.cqc01` `data.cqc02` `data.cqc03` `data.cqc04` `data.cqc05`	More Datasets and Examples (Similar to ConQuest Examples)
`data.ctest1` `data.ctest2`	Some C-Test Datasets
`data.ex08` `data.ex10` `data.ex11` `data.ex12` `data.ex14` `data.ex15` `data.exJ03`	Datasets `data.ex` in TAM Package
`data.fims.Aus.Jpn.raw` `data.fims.Aus.Jpn.scored`	Dataset FIMS Study with Responses of Australian and Japanese Students
`data.geiser`	Dataset from Geiser et al. (2006)
`data.gpcm`	Dataset with Ordered Indicators
`data.janssen` `data.janssen2`	Dataset from Janssen and Geiser (2010)
`data.mc`	Dataset with Raw and Scored Responses from Multiple Choice Items
`data.numeracy`	Dataset Numeracy
`data.sim.mfr` `data.sim.facets`	Simulated Multifaceted Data
`data.sim.rasch` `data.sim.rasch.pweights` `data.sim.rasch.missing`	Simulated Rasch data
`data.timssAusTwn` `data.timssAusTwn.scored`	Dataset TIMSS 2011 of Australian and Taiwanese Students
`DescribeBy()`	S3 Method for Descriptive Statistics of Objects
`designMatrices()` `print(<designMatrices>)` `designMatrices.mfr()` `designMatrices.mfr2()` `.A.matrix()` `rownames.design()` `.A.PCM2()` `.A.PCM3()`	Generation of Design Matrices
`doparse()`	Parsing a String with `DO` Statements
`IRT.cv()`	Cross-Validation of a Fitted IRT Model
`IRT.data(<tam.mml>)` `IRT.data(<tam.mml.3pl>)` `IRT.data(<tamaan>)`	Extracting Item Response Dataset
`IRT.drawPV()`	Function for Drawing Plausible Values
`IRT.expectedCounts(<tam>)` `IRT.expectedCounts(<tam.mml>)` `IRT.expectedCounts(<tam.mml.3pl>)` `IRT.expectedCounts(<tamaan>)` `IRT.expectedCounts(<tam.np>)`	Extracting Expected Counts
`IRT.factor.scores(<tam>)` `IRT.factor.scores(<tam.mml>)` `IRT.factor.scores(<tam.mml.3pl>)` `IRT.factor.scores(<tamaan>)`	Extracting Factor Scores in TAM
`IRT.frequencies(<tam.mml>)` `IRT.frequencies(<tam.mml.3pl>)` `IRT.frequencies(<tamaan>)`	Observed and Expected Frequencies for Univariate and Bivariate Distributions
`IRT.informationCurves()` `plot(<IRT.informationCurves>)`	Item and Test Information Curve
`IRT.irfprob(<tam>)` `IRT.irfprob(<tam.mml>)` `IRT.irfprob(<tam.mml.3pl>)` `IRT.irfprob(<tamaan>)` `IRT.irfprob(<tam.np>)`	Extracting Item Response Functions
`IRT.itemfit(<tam.mml>)` `IRT.itemfit(<tam.mml.2pl>)` `IRT.itemfit(<tam.mml.mfr>)` `IRT.itemfit(<tam.mml.3pl>)`	RMSD Item Fit Statistics for TAM Objects
`IRT.likelihood(<tam>)` `IRT.posterior(<tam>)` `IRT.likelihood(<tam.mml>)` `IRT.posterior(<tam.mml>)` `IRT.likelihood(<tam.mml.3pl>)` `IRT.posterior(<tam.mml.3pl>)` `IRT.likelihood(<tamaan>)` `IRT.posterior(<tamaan>)` `IRT.likelihood(<tam.latreg>)` `IRT.posterior(<tam.latreg>)` `IRT.likelihood(<tam.np>)` `IRT.posterior(<tam.np>)`	Extracting Individual Likelihood and Individual Posterior
`IRT.linearCFA()` `summary(<IRT.linearCFA>)`	Linear Approximation of a Confirmatory Factor Analysis
`IRT.residuals()` `residuals(<tam.mml>)` `residuals(<tam.mml.2pl>)` `residuals(<tam.mml.mfr>)` `residuals(<tam.jml>)`	Residuals in an IRT Model
`IRT.simulate()`	Simulating Item Response Models
`IRT.threshold()` `print(<IRT.threshold>)` `IRT.WrightMap()`	Thurstonian Thresholds and Wright Map for Item Response Models
`IRT.truescore()`	Converts a \(\theta\) Score into a True Score \(\tau ( \theta)\)
`IRT.WrightMap(<tam.mml>)` `IRT.WrightMap(<tamaan>)`	Wright Map for Item Response Models by Using the WrightMap Package
`IRTLikelihood.cfa()`	Individual Likelihood for Confirmatory Factor Analysis
`IRTLikelihood.ctt()`	Computes Individual Likelihood from Classical Test Theory Estimates
`lavaanify.IRT()`	Slight Extension of the `lavaan` Syntax, with Focus on Item Response Models
`msq.itemfit()` `summary(<msq.itemfit>)` `msq.itemfitWLE()` `summary(<msq.itemfitWLE>)`	Mean Squared Residual Based Item Fit Statistics (Infit, Outfit)
`plot(<tam>)` `plot(<tam.mml>)` `plot(<tam.jml>)`	Plot Function for Unidimensional Item Response Models
`plotDevianceTAM()`	Deviance Plot for TAM Objects
`predict(<tam.mml>)` `predict(<tam.mml.3pl>)` `predict(<tamaan>)`	Expected Values and Predicted Probabilities for Fitted TAM Models
`Scale()`	S3 Method for Standardizations and Transformations of Variables
`tam.jml2()`	Defunct TAM Functions
`TAM-package` `TAM`	Test Analysis Modules
`IRT.RISE()` `tam_model_implied_means()` `tam_packageinfo()` `tam_print_call()` `tam_rsessinfo()` `tam_args_CALL_search()` `require_namespace_msg()` `add.lead()` `tam_round_data_frame()` `tam_round_data_frame_print()` `tam_osink()` `tam_csink()` `tam_matrix2()` `tam_outer()` `tam_normalize_matrix_rows()` `tam_normalize_vector()` `tam_aggregate()` `tam_interval_index()` `tam_rowCumsums()` `tam_dmvnorm()` `tam_bayesian_bootstrap()` `tam_cov_wt()` `tam_cor_wt()` `tam_ginv()` `tam_ginv_scaled()` `tam_remove_missings()` `tam_AXsi_compute()` `tam_AXsi_fit()` `tam_max_abs()` `tam_max_abs_list()` `tam_trim_increment()` `tam_difference_quotient()` `tam_assign_list_elements()`	Utility Functions in TAM
`tam.ctt()` `tam.ctt2()` `tam.ctt3()` `tam.cb()` `plotctt()`	Classical Test Theory Based Statistics and Plots
`tam.fa()`	Bifactor Model and Exploratory Factor Analysis
`tam.fit()` `tam.mml.fit()` `tam.jml.fit()` `summary(<tam.fit>)`	Item Infit and Outfit Statistic
`tam.jml()` `summary(<tam.jml>)` `logLik(<tam.jml>)`	Joint Maximum Likelihood Estimation
`tam.latreg()` `summary(<tam.latreg>)` `print(<tam.latreg>)`	Latent Regression Model
`tam.linking()` `summary(<tam.linking>)` `print(<tam.linking>)` `tam_linking_2studies()` `summary(<tam_linking_2studies>)` `print(<tam_linking_2studies>)`	Linking of Fitted Unidimensional Item Response Models in TAM
`tam.mml.3pl()` `summary(<tam.mml.3pl>)` `print(<tam.mml.3pl>)`	3PL Structured Item Response Model in TAM
`tam()` `tam.mml()` `tam.mml.2pl()` `tam.mml.mfr()` `summary(<tam>)` `summary(<tam.mml>)` `print(<tam>)` `print(<tam.mml>)`	Test Analysis Modules: Marginal Maximum Likelihood Estimation
`tam.modelfit()` `summary(<tam.modelfit>)` `IRT.modelfit(<tam.mml>)` `IRT.modelfit(<tam.mml.3pl>)` `IRT.modelfit(<tamaan>)` `summary(<IRT.modelfit.tam.mml>)` `summary(<IRT.modelfit.tam.mml.3pl>)` `summary(<IRT.modelfit.tamaan>)` `tam.modelfit.IRT()` `tam.modelfit.args()` `tam.Q3()` `summary(<tam.Q3>)`	Model Fit Statistics in TAM
`tam.np()` `summary(<tam.np>)` `IRT.cv(<tam.np>)`	Unidimensional Non- and Semiparametric Item Response Model
`tam.personfit()`	Person Outfit and Infit Statistics
`tam.pv()` `tam.pv.mcmc()` `summary(<tam.pv.mcmc>)` `plot(<tam.pv.mcmc>)`	Plausible Value Imputation
`tam.se()` `tam_mml_se_quick()` `tam_latreg_se_quick()`	Standard Error Estimation
`tam.threshold()`	Calculation of Thurstonian Thresholds
`tam.wle()` `tam.mml.wle()` `tam.mml.wle2()` `tam_jml_wle()` `summary(<tam.wle>)` `print(<tam.wle>)`	Weighted Likelihood Estimation and Maximum Likelihood Estimation of Person Parameters
`tamaan()` `summary(<tamaan>)` `print(<tamaan>)`	Wrapper Function for TAM Language
`tamaanify()`	Function for Parsing TAM Input
`tampv2datalist()`	Conversion of Plausible Value Object into Datalist
`tam_downcode()`	Downcoding an Item Response Dataset
`tam_irf_3pl()`	Item Response Function for the 3PL Model
`tam_NA_pattern()` `tam_01_pattern()`	Missing Data Patterns
`weighted_mean()` `weighted_var()` `weighted_sd()` `weighted_skewness()` `weighted_kurtosis()` `weighted_quantile()` `weighted_table()`	Descriptive Statistics for Weighted Data
`WLErel()` `EAPrel()`	Reliability Estimation in TAM

Reference

All functions