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High-dimensional maximum marginal likelihood item factor analysis by adaptive quadrature

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  • Stephen Schilling
  • R. Bock

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  • Stephen Schilling & R. Bock, 2005. "High-dimensional maximum marginal likelihood item factor analysis by adaptive quadrature," Psychometrika, Springer;The Psychometric Society, vol. 70(3), pages 533-555, September.
    • Handle: RePEc:spr:psycho:v:70:y:2005:i:3:p:533-555
    DOI: 10.1007/s11336-003-1141-x
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    References listed on IDEAS

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    1. Henry Kaiser, 1958. "The varimax criterion for analytic rotation in factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 23(3), pages 187-200, September.
    2. Rabe-Hesketh, Sophia & Skrondal, Anders & Pickles, Andrew, 2005. "Maximum likelihood estimation of limited and discrete dependent variable models with nested random effects," Journal of Econometrics, Elsevier, vol. 128(2), pages 301-323, October.
    3. Sophia Rabe-Hesketh & Anders Skrondal & Andrew Pickles, 2002. "Reliable estimation of generalized linear mixed models using adaptive quadrature," Stata Journal, StataCorp LP, vol. 2(1), pages 1-21, February.
    4. George Ferguson, 1941. "The factorial interpretation of test difficulty," Psychometrika, Springer;The Psychometric Society, vol. 6(5), pages 323-329, October.
    5. J. Guilford, 1941. "The difficulty of a test and its factor composition," Psychometrika, Springer;The Psychometric Society, vol. 6(2), pages 67-77, April.
    6. J. C. Naylor & A. F. M. Smith, 1982. "Applications of a Method for the Efficient Computation of Posterior Distributions," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 31(3), pages 214-225, November.
    7. Emmanuel Lesaffre & Bart Spiessens, 2001. "On the effect of the number of quadrature points in a logistic random effects model: an example," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 50(3), pages 325-335.
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