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 11 articles )

Showing results 1 to 11 of 11.
Sorted by year (citations)

  1. Battauz, Michela: Multiple equating of separate IRT calibrations (2017)
  2. 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)
  3. 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)
  4. Bartolucci, Francesco; Bacci, Silvia; Gnaldi, Michela: Statistical analysis of questionnaires. A unified approach based on R and Stata (2016)
  5. Ip, Edward H.; Chen, Shyh-Huei; Quandt, Sara A.: Analysis of multiple partially ordered responses to belief items with don’t know option (2016)
  6. Nikoloulopoulos, Aristidis K.; Joe, Harry: Factor copula models for item response data (2015)
  7. Strobl, Carolin; Kopf, Julia; Zeileis, Achim: Rasch trees: a new method for detecting differential item functioning in the Rasch model (2015)
  8. Karl, Andrew T.; Eubank, Randy; Milovanovic, Jelena; Reiser, Mark; Young, Dennis: Using rngstreams for parallel random number generation in C++ and R (2014)
  9. Battauz, Michela: IRT test equating in complex linkage plans (2013)
  10. San Martín, Ernesto; Rolin, Jean-Marie; Castro, Luis M.: Identification of the 1PL model with guessing parameter: parametric and semi-parametric results (2013)
  11. Bertrand, Daisy; El Ahmadi, Abdessadek; Heuchenne, Christian: From a Guttman ordinal scale to a Rasch ratio scale (2008)