We consider optimal designs for a class of symmetric models for binary data which includes the common probit and logit models. We show that for a large group of optimality criteria which includes the ...

The flexibility and power that probit and logit models bring to the table suggest that running the numbers through these filters should be on everyone's short list of analytical tools.

The principal models examined in the course are binary logit and probit, multinomial logit, ordinal logit and probit, tobit, and the family of Poisson regression models. The Heckman correction for ...

Mixed logit (MXL) is a general discrete choice model thus far unexamined in the study of multicandidate and multiparty elections. Mixed logit assumes that the unobserved portions of utility are a ...

We compare how logit (fixed effects) and probit early warning systems (EWS) predict insample and out-of-sample currency crises in emerging markets (EMs). We look at episodes of currency crises that ...