We show that with a simple normalization of explanatory variables, marginal effects in probit and logit models simplify dramatically, becoming a function of only the estimated constant term. Related simplifications hold for computation of asymptotic variances of these effects. D 2003 Elsevier B.V. All rights reserved.

Saddlepoint approximations of marginal densities and tail probabilities of general nonlinear statistics are derived. They are based on the expansion of the statistic up to the second order. Their accuracy is shown in a variety of examples, including logit and probit models and rank estimators for regression.

despite controversy, the contingent valuation method (cvm) is widely used for non-market valuation. among elicitation methods of cvm, the dichotomous choice (dc) has been paid attention. there are two types of dc methods: single-bounded dc (sbdc) and double-bounded dc (dbdc). dbdc is more efficient than sbdc. many of cvm studies in iran used dbdc but data analyses were done by logit model; that...

Ordered discrete dependent variable models such as ordered probit and ordered logit are frequently used across the social sciences to study outcomes including health status, happiness, wealth and educational attainment. Unlike in the case of OLS, unaccounted for heteroskedasticity in these models can lead to biased parameter estimates. This paper introduces the oglmx package for the R statistic...

Alternative parameterizations and problems of identification and estimation of multivariate random effects models for categorical responses are investigated. The issues are illustrated in the context of the multivariate binomial logit-normal (BLN) model introduced by Coull and Agresti (2000, Biometrics 56, 73-80). We demonstrate that the BLN model is poorly identified unless proper restrictions...

Predicting default probabilities is at the core of credit risk management and is becoming more and more important for banks in order to measure their client’s degree of risk, and for firms to operate successfully. The SVM with evolutionary feature selection is applied to the CreditReform database. We use classical methods such as discriminan analysis (DA), logit and probit models as benchmark O...

Most discussions of ordinal variables in the sociological literature debate the suitability of linear regression and structural equation methods when some variables are ordinal. Largely ignored in these discussions are methods for ordinal variables that are natural extensions of probit and logit models for dichotomous variables. If ordinal variables are discrete realizations of unmeasured conti...

DCM (Discrete Choice Models) is a package, written in Ox, for estimating a class of discrete choice models. DCM represents an important development for both the OxMetric and, more generally, microeconometric computing environment in making available a broad range of discrete choice models, including standard binary response models, with notable extensions including conditional mixed logit, mixe...