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Markov chain Monte Carlo exact inference for binomial and multinomial logistic regression models

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Abstract

We develop Metropolis-Hastings algorithms for exact conditional inference, including goodness-of-fit tests, confidence intervals and residual analysis, for binomial and multinomial logistic regression models. We present examples where the exact results, obtained by enumeration, are available for comparison. We also present examples where Monte Carlo methods provide the only feasible approach for exact inference.

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Forster, J.J., McDonald, J.W. & Smith, P.W.F. Markov chain Monte Carlo exact inference for binomial and multinomial logistic regression models. Statistics and Computing 13, 169–177 (2003). https://doi.org/10.1023/A:1023212726863

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  • DOI: https://doi.org/10.1023/A:1023212726863

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