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On the numerical approximation of the bivariate normal (tetrachoric) correlation coefficient

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  • David Kirk

Abstract

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Suggested Citation

  • David Kirk, 1973. "On the numerical approximation of the bivariate normal (tetrachoric) correlation coefficient," Psychometrika, Springer;The Psychometric Society, vol. 38(2), pages 259-268, June.
  • Handle: RePEc:spr:psycho:v:38:y:1973:i:2:p:259-268
    DOI: 10.1007/BF02291118
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    Cited by:

    1. Battauz, Michela & Vidoni, Paolo, 2022. "A likelihood-based boosting algorithm for factor analysis models with binary data," Computational Statistics & Data Analysis, Elsevier, vol. 168(C).
    2. Golob, Thomas F. & Regan, A C, 1999. "Freight Industry Attitudes Towards Policies to Reduce Congestion," University of California Transportation Center, Working Papers qt57r4d3fd, University of California Transportation Center.
    3. Golob, Thomas F. & Reagan, Amelia C., 2002. "Trucking Industry Adoption of Information Technology: A structural Multivariate Discrete Choice Model," University of California Transportation Center, Working Papers qt7kv5f17n, University of California Transportation Center.
    4. Sarah M. Lein & Eva Köberl, 2009. "Capacity Utilisation, Constraints and Price Adjustments under the Microscope," Working Papers 2009-06, Swiss National Bank.
    5. Golob, Thomas F. & Regan, A C, 2002. "Trucking Industry Adoption of Information Technology: A Structural Multivariate Probit Model," University of California Transportation Center, Working Papers qt9w1988t7, University of California Transportation Center.
    6. Bengt Muthén & Charles Hofacker, 1988. "Testing the assumptions underlying tetrachoric correlations," Psychometrika, Springer;The Psychometric Society, vol. 53(4), pages 563-577, December.
    7. Golob, Thomas F. & Regan, Amelia C., 1999. "Freight industry attitudes towards policies to reduce congestion," University of California Transportation Center, Working Papers qt3fq6x2sq, University of California Transportation Center.
    8. Taban Baghfalaki & Mojtaba Ganjali, 2020. "A transition model for analyzing multivariate longitudinal data using Gaussian copula approach," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 104(2), pages 169-223, June.

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