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An Aggregate IRT Procedure for Exploratory Factor Analysis

Author

Listed:
  • Gregory Camilli

    (Rutgers, The State University of New Jersey)

  • Jean-Paul Fox

    (University of Twente)

Abstract

An aggregation strategy is proposed to potentially address practical limitation related to computing resources for two-level multidimensional item response theory (MIRT) models with large data sets. The aggregate model is derived by integration of the normal ogive model, and an adaptation of the stochastic approximation expectation maximization algorithm is used for estimation. This methodology is used to conduct an exploratory factor analysis of the 2007 mathematics data from Trends in International Mathematics and Science Study (TIMSS) fourth grade to illustrate potential uses. A comparison to flexMIRT and two brief simulations indicate the aggregate model provides accurate estimates of Level 2 parameters despite loss of information ensuing from key assumption.

Suggested Citation

  • Gregory Camilli & Jean-Paul Fox, 2015. "An Aggregate IRT Procedure for Exploratory Factor Analysis," Journal of Educational and Behavioral Statistics, , vol. 40(4), pages 377-401, August.
    • Handle: RePEc:sae:jedbes:v:40:y:2015:i:4:p:377-401
    DOI: 10.3102/1076998615589185
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    References listed on IDEAS

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