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Psychoco: Psychometric Computing in R

Author

Listed:
  • Wickelmaier, Florian
  • Strobl, Carolin
  • Zeileis, Achim

Abstract

This special volume features eleven contributions to psychometric computing, a research area that integrates psychometrics and computational methods in statistics. Topics covered include structural equation modeling, item response theory, probabilistic choice modeling, and other modeling approaches prevalent in or useful for psychometric research. Each contributed paper is accompanied by a software package published on the Comprehensive R Archive Network. This introduction gives a brief overview of the volume.

Suggested Citation

  • Wickelmaier, Florian & Strobl, Carolin & Zeileis, Achim, 2012. "Psychoco: Psychometric Computing in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i01).
    • Handle: RePEc:jss:jstsof:v:048:i01
    DOI: http://hdl.handle.net/10.18637/jss.v048.i01
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    References listed on IDEAS

    as
    1. Epskamp, Sacha & Cramer, Angélique O.J. & Waldorp, Lourens J. & Schmittmann, Verena D. & Borsboom, Denny, 2012. "qgraph: Network Visualizations of Relationships in Psychometric Data," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i04).
    2. van der Ark, L. Andries, 2007. "Mokken Scale Analysis in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 20(i11).
    3. 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).
    4. de Leeuw, Jan & Mair, Patrick, 2007. "An Introduction to the Special Volume on "Psychometrics in R"," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 20(i01).
    5. Monecke, Armin & Leisch, Friedrich, 2012. "semPLS: Structural Equation Modeling Using Partial Least Squares," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i03).
    6. Turner, Heather & Firth, David, 2012. "Bradley-Terry Models in R: The BradleyTerry2 Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i09).
    7. Firth, David, 2005. "Bradley-Terry Models in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 12(i01).
    8. Rosseel, Yves, 2012. "lavaan: An R Package for Structural Equation Modeling," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i02).
    9. Hatzinger, Reinhold & Dittrich, Regina, 2012. "prefmod: An R Package for Modeling Preferences Based on Paired Comparisons, Rankings, or Ratings," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i10).
    10. Magis, David & Raîche, Gilles, 2012. "Random Generation of Response Patterns under Computerized Adaptive Testing with the R Package catR," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i08).
    11. Doran, Harold & Bates, Douglas & Bliese, Paul & Dowling, Maritza, 2007. "Estimating the Multilevel Rasch Model: With the lme4 Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 20(i02).
    12. 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).
    13. van der Ark, L. Andries, 2012. "New Developments in Mokken Scale Analysis in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i05).
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    Cited by:

    1. Mazza, Angelo & Punzo, Antonio & McGuire, Brian, 2014. "KernSmoothIRT: An R Package for Kernel Smoothing in Item Response Theory," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 58(i06).

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