1 SUMMARY The development of adequate models for binary time series data with covariate adjustment has been an active research area in the last years. In the case, where interest is focused on marginal and association parameters, generalized estimating equations (GEE) (see for example Lipsitz, Laird and Harrington (1991) and Liang, Zeger and Qaqish (1992)) and likelihood (see for example Fitzma...

This study analyzes the demand for cigarettes …tting observed zero outcomes with a trivariate model consisting of an equation for the starting smoking decision, an equation for the quitting decision, and an equation that models the level of cigarettes consumed. Five competing speci…cations are considered to explain level, with the ordered probit, which accommodates pile-ups of counts in the dep...

We introduce a generalized skew probit (gsp) class of links for the modeling of binary regression giving some properties and conditions for the existence of the maximum likelihood estimator and of the posterior distributions of the parameters of the model when improper uniform priors are established. As shown, asymmetric links already proposed in the literature are special cases of the general ...

A simulation study designed to evaluate the pseudo-R2T proposed in an earlier paper by Spiess and Keller suggests that, for the models considered, this measure represents the goodness of fit not only of the systematic part, but also of the assumed correlation structure in binary panel probit models.

http://www.jstor.org A Correlated Probit Model for Joint Modeling of Clustered Binary and Continuous Responses Author(s): Ralitza V. Gueorguieva and Alan Agresti Source: Journal of the American Statistical Association, Vol. 96, No. 455 (Sep., 2001), pp. 11021112 Published by: on behalf of the Taylor & Francis, Ltd. American Statistical Association Stable URL: http://www.jstor.org/stable/2670256...

The maximum likelihood estimates of a principal component analysis on the logit or probit scale are computed using majorization algorithms that iterate a sequence of weighted or unweighted singular value decompositions. The relation with similar methods in item response theory, roll call analysis, and binary choice analysis is discussed. The technique is applied to 2001 US House roll call data.

Poirier (1980, JoE) considered a bivariate probit model in which the binary dependent variables y 1 and y 2 were not observed individually, but the product z = y 1 @y 2 was observed. This paper expands this notion of partial observability to multivariate settings.

In this paper we introduce new robust estimators for the logistic and probit regressions for binary, multinomial, nominal and ordinal data and apply these models to estimate the parameters when outliers or inluential observations are present. Maximum likelihood estimates don't behave well when outliers or inluential observations are present. One remedy is to remove inluential observations from ...

Corporate directors are influenced by overconfidence, which is one of the personality traits of individuals; it may take irrational decisions that will have a significant impact on the company's performance in the long run. The purpose of this paper is to validate and compare the Naive Bayesian Classification algorithm and probit regression in the prediction of Management's overconfident at pre...

We consider analysis of relational data (a matrix), in which the rows correspond to subjects (e.g., people) and the columns correspond to attributes. The elements of the matrix may be a mix of real and categorical. Each subject and attribute is characterized by a latent binary feature vector, and an inferred matrix maps each row-column pair of binary feature vectors to an observed matrix elemen...