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TAM (version 1.6-0)

Test Analysis Modules

Description

Includes marginal and joint maximum likelihood estimation of uni- and multidimensional item response models (Rasch, 2PL, 3PL, Generalized Partial Credit, Multi Facets, Nominal Item Response, Structured Latent Class Analysis, Mixture Distribution IRT Models, Located Latent Class Models, Cognitive Diagnostic Models). Latent regression models and plausible value imputation are also supported.

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Version

Install

install.packages('TAM')

Monthly Downloads

3,732

Version

1.6-0

License

GPL (>= 2)

Homepage

http://www.edmeasurementsurveys.com/TAM/Tutorials/

Maintainer

Alexander Robitzsch

Last Published

April 3rd, 2015

Functions in TAM (1.6-0)

Linear Approximation of a Confirmatory Factor Analysis

IRT.factor.scores

Extracting Factor Scores in TAM

Extracting Item Response Dataset

Weighted Likelihood Estimation and Maximum Likelihood Estimation of Person Parameters

Extracting Item Response Functions

Thurstonian Thresholds and Wright Map for Item Response Models

Expected Values and Predicted Probabilities for Fitted TAM Models

Test Analysis Modules

Likelihood Ratio Test for Model Comparisons and Log-Likelihood Value

Dataset from Janssen and Geiser (2010)

Dataset with Ordered Indicators

Computation of intermediate information

plotDevianceTAM

Deviance Plot for TAM Objects

Simulated Multifaceted Data

Function for Drawing Plausible Values

IRTLikelihood.cfa

Individual Likelihood for Confirmatory Factor Analysis

Dataset with Raw and Scored Responses from Multiple Choice Items

Wright Map for Item Response Models by Using the WrightMap Package

Dataset Numeracy

Dataset from Geiser et al. (2006)

Slight Extension of the lavaan Syntax, with Focus on Item Response Models

Conversion of Plausible Value Object into Datalist

3PL Structured Item Response Model in TAM

Wrapper Function for TAM Language

Datasets data.ex in TAM Package

Joint Maximum Likelihood Estimation

Some C-Test Datasets

Simulated Rasch data

Calculation of Thurstonian Thresholds

Classical Test Theory Based Statistics and Plots

Plausible Value Imputation

Model Fit Statistics in TAM

Latent Regression Model

IRT.expectedCounts

Extracting Expected Counts

Parsing a String with DO Statements

Standard Error Estimation

Item Infit and Outfit Statistic

Bifactor Model and Exploratory Factor Analysis

Generation of Design Matrices

Test Analysis Modules: Marginal Maximum Likelihood Estimation

data.timssAusTwn

Dataset TIMSS 2011 of Australian and Taiwanese Students

Extracting Individual Likelihood and Individual Posterior

More Datasets and Examples (Similar to ConQuest Examples)

data.fims.Aus.Jpn.scored

Dataset FIMS Study with Responses of Australian and Japanese Students

Plot Function for Unidimensional Item Response Models

Function for Parsing TAM Input

cfa.extract.itempars

Extracting Item Parameters from a Fitted cfa Object

Mean Squared Residual Based Item Fit Statistics (Infit, Outfit)