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Approximate inference for the multinomial logit model

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  • Rekkas, M.

Abstract

Higher-order asymptotic theory is used to derive p-values that achieve superior accuracy compared to the p-values obtained from traditional tests for inference about parameters of the multinomial logit model. Simulations are provided to assess the finite sample behavior of the test statistics considered and to demonstrate the superiority of the higher-order method. Stata code that outputs these p-values is available to facilitate the implementation of these methods for the end-user.

Suggested Citation

  • Rekkas, M., 2009. "Approximate inference for the multinomial logit model," Statistics & Probability Letters, Elsevier, vol. 79(2), pages 237-242, January.
    • Handle: RePEc:eee:stapro:v:79:y:2009:i:2:p:237-242
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    References listed on IDEAS

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    1. A. C. Davison & D. A. S. Fraser & N. Reid, 2006. "Improved likelihood inference for discrete data," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 68(3), pages 495-508, June.
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