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ltm: An R Package for Latent Variable Modeling and Item Response Analysis

Author

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  • Rizopoulos, Dimitris

Abstract

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.

Suggested Citation

  • Rizopoulos, Dimitris, 2006. "ltm: An R Package for Latent Variable Modeling and Item Response Analysis," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 17(i05).
  • Handle: RePEc:jss:jstsof:v:017:i05
    DOI: http://hdl.handle.net/10.18637/jss.v017.i05
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    Citations

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    Cited by:

    1. Frick, Hannah & Strobl, Carolin & Leisch, Friedrich & Zeileis, Achim, 2012. "Flexible Rasch Mixture Models with Package psychomix," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i07).
    2. Isabella Sulis & Mariano Porcu, 2015. "Assessing Divergences in Mathematics and Reading Achievement in Italian Primary Schools: A Proposal of Adjusted Indicators of School Effectiveness," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 122(2), pages 607-634, June.
    3. repec:jss:jstsof:v:076:i05 is not listed on IDEAS
    4. Yang Liu & Ji Seung Yang, 2018. "Bootstrap-Calibrated Interval Estimates for Latent Variable Scores in Item Response Theory," Psychometrika, Springer;The Psychometric Society, vol. 83(2), pages 333-354, June.
    5. Jean-Benoit Hardouin, 2007. "Rasch analysis: Estimation and tests with raschtest," Stata Journal, StataCorp LP, vol. 7(1), pages 22-44, February.
    6. Grand, James A. & Golubovich, Juliya & Ryan, Ann Marie & Schmitt, Neal, 2013. "The detection and influence of problematic item content in ability tests: An examination of sensitivity review practices for personnel selection test development," Organizational Behavior and Human Decision Processes, Elsevier, vol. 121(2), pages 158-173.
    7. Brian O’Connor & Maxine Crawford & Mark Holder, 2015. "An Item Response Theory Analysis of the Subjective Happiness Scale," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 124(1), pages 249-258, October.
    8. Edward H. Ip & Shyh-Huei Chen & Sara A. Quandt, 2016. "Analysis of Multiple Partially Ordered Responses to Belief Items with Don’t Know Option," Psychometrika, Springer;The Psychometric Society, vol. 81(2), pages 483-505, June.
    9. Andrew Karl & Randy Eubank & Jelena Milovanovic & Mark Reiser & Dennis Young, 2014. "Using RngStreams for parallel random number generation in C++ and R," Computational Statistics, Springer, vol. 29(5), pages 1301-1320, October.
    10. Xiang Liu & Zhuangzhuang Han & Matthew S. Johnson, 2018. "The UMP Exact Test and the Confidence Interval for Person Parameters in IRT Models," Psychometrika, Springer;The Psychometric Society, vol. 83(1), pages 182-202, March.
    11. Michela Battauz, 2015. "Factors affecting the variability of IRT equating coefficients," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 69(2), pages 85-101, May.
    12. W. W. Koczkodaj & T. Kakiashvili & A. Szymańska & J. Montero-Marin & R. Araya & J. Garcia-Campayo & K. Rutkowski & D. Strzałka, 2017. "How to reduce the number of rating scale items without predictability loss?," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(2), pages 581-593, May.
    13. Chalmers, R. Philip, 2012. "mirt: A Multidimensional Item Response Theory Package for the R Environment," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i06).
    14. repec:spr:stmapp:v:28:y:2019:i:1:d:10.1007_s10260-018-00442-w is not listed on IDEAS
    15. Sora Lee & Daniel M. Bolt, 2018. "Asymmetric Item Characteristic Curves and Item Complexity: Insights from Simulation and Real Data Analyses," Psychometrika, Springer;The Psychometric Society, vol. 83(2), pages 453-475, June.
    16. repec:bpj:jossai:v:2:y:2014:i:5:p:437-450:n:5 is not listed on IDEAS
    17. Carolin Strobl & Julia Kopf & Achim Zeileis, 2015. "Rasch Trees: A New Method for Detecting Differential Item Functioning in the Rasch Model," Psychometrika, Springer;The Psychometric Society, vol. 80(2), pages 289-316, June.
    18. Fabrizio Maturo & Francesca Fortuna & Tonio Di Battista, 2019. "Testing Equality of Functions Across Multiple Experimental Conditions for Different Ability Levels in the IRT Context: The Case of the IPRASE TLT 2016 Survey," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 146(1), pages 19-39, November.

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