Logistic regression model maximum likelihood estimation

Haines et al. (47) suggested including the criterion Bayesian D-optimality, which maximizes some concave function of the information matrix, which in essence is the minimization of the generalized variance of the maximum likelihood estimators of the two parameters of the logistic regression. The authors underline that toxicity is recorded as an ordinal variable and not a simple binary variable, and that the present design needs to be extended to proportional odds models. 

Maximum Likelihood Estimation in the Logistic Regression Model... 

The frequentist approach to estimation in the logistic regression model would be to find the maximum likelihood estimators. They would be the simultaneous solutions of... 

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