ltm

ltm: an R package for latent variable modelling and item response theory analyses. The R package ltm has been developed for the analysis of multivariate dichotomous and polytomous data using latent variable models, under the Item Response Theory approach. For dichotomous data the Rasch, the Two-Parameter Logistic, and Birnbaum’s Three-Parameter models have been implemented, whereas for polytomous data Semejima’s Graded Response model is available. Parameter estimates are obtained under marginal maximum likelihood using the Gauss-Hermite quadrature rule. The capabilities and features of the package are illustrated using two real data examples.

This software is also peer reviewed by journal JSS.


References in zbMATH (referenced in 23 articles )

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  1. Liu, Xiang; Han, Zhuangzhuang; Johnson, Matthew S.: The UMP exact test and the confidence interval for person parameters in IRT models (2018)
  2. Battauz, Michela: Multiple equating of separate IRT calibrations (2017)
  3. Ordóñez Galán, Celestino; Sánchez Lasheras, Fernando; de Cos Juez, Francisco Javier; Bernardo Sánchez, Antonio: Missing data imputation of questionnaires by means of genetic algorithms with different fitness functions (2017)
  4. Sulis, Isabella; Porcu, Mariano: Handling missing data in item response theory. Assessing the accuracy of a multiple imputation procedure based on latent class analysis (2017)
  5. Víctor Cervantes: DFIT: An R Package for Raju’s Differential Functioning of Items and Tests Framework (2017)
  6. Bartolucci, Francesco; Bacci, Silvia; Gnaldi, Michela: Statistical analysis of questionnaires. A unified approach based on R and Stata (2016)
  7. Ip, Edward H.; Chen, Shyh-Huei; Quandt, Sara A.: Analysis of multiple partially ordered responses to belief items with don’t know option (2016)
  8. Jorge Tendeiro and Rob Meijer and A. Niessen: PerFit: An R Package for Person-Fit Analysis in IRT (2016)
  9. Dylan Molenaar;Francis Tuerlinckx; Han van der Maas: Fitting Diffusion Item Response Theory Models for Responses and Response Times Using the R Package diffIRT (2015)
  10. Michela Battauz: equateIRT: An R Package for IRT Test Equating (2015)
  11. Nikoloulopoulos, Aristidis K.; Joe, Harry: Factor copula models for item response data (2015)
  12. Strobl, Carolin; Kopf, Julia; Zeileis, Achim: Rasch trees: a new method for detecting differential item functioning in the Rasch model (2015)
  13. Karl, Andrew T.; Eubank, Randy; Milovanovic, Jelena; Reiser, Mark; Young, Dennis: Using rngstreams for parallel random number generation in C++ and R (2014)
  14. Battauz, Michela: IRT test equating in complex linkage plans (2013)
  15. San Martín, Ernesto; Rolin, Jean-Marie; Castro, Luis M.: Identification of the 1PL model with guessing parameter: parametric and semi-parametric results (2013)
  16. Hannah Frick; Carolin Strobl; Friedrich Leisch; Achim Zeileis: Flexible Rasch Mixture Models with Package psychomix (2012)
  17. R. Chalmers: mirt: A Multidimensional Item Response Theory Package for the R Environment (2012)
  18. Paul De Boeck; Marjan Bakker; Robert Zwitser; Michel Nivard; Abe Hofman; Francis Tuerlinckx; Ivailo Partchev: The Estimation of Item Response Models with the lmer Function from the lme4 Package in R (2011)
  19. Seung Choi; Laura Gibbons; Paul Crane: lordif: An R Package for Detecting Differential Item Functioning Using Iterative Hybrid Ordinal Logistic Regression/Item Response Theory and Monte Carlo Simulations (2011)
  20. Ali Ünlü; Anatol Sargin: DAKS: An R Package for Data Analysis Methods in Knowledge Space Theory (2010)

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