Maximum likelihood estimation in binary data models using panel data under alternative distributional assumptions

This paper considers an alternative to the commonly used random effects probit model. The likelihood does not require numerical integration and expressions for the score and hessian are provided. The possible diagnostic use of the model is illustrated.