In this paper we examine theoretically and by simulation whether or not unobserved heterogeneity independent of the included regressors is really an issue in logit, probit and loglog models with both binary and fractional data. We found that unobserved heterogeneity: (i) produces an attenuation bias in the estimation of regression coefficients; (ii) is innocuous for logit estimation of average ...

This paper explains how to calculate adjusted risk ratios and risk differences when reporting results from logit, probit, and related nonlinear models. Building on Stata’s margins command, we create a new post-estimation command adjrr that calculates adjusted risk ratios (ARR) and adjusted risk differences (ARD) after running logit or probit models with either binary, multinomial, or ordered ou...

The Blinder-Oaxaca decomposition technique is widely used to identify and quantify the separate contributions of group differences in measurable characteristics, such as education, experience, marital status, and geographical differences to racial and gender gaps in outcomes. The technique cannot be used directly, however, if the outcome is binary and the coefficients are from a logit or probit...

This paper considers two recently proposed semiparametric estimators for distribution-free binary response models under a conditional median restriction. It shows that these estimators can be implemented in Stata using nl through simple modifications to the nonlinear least squares probit criterion function. We then introduce dfbr, a new Stata command which implements these estimators, and provi...

We use a binary and a multinomial probit model to describe the Dutch household moving decision and joint decisions of the housing tenure choice and residential mobility, respectively. We can only observe the change of the tenure choice after the household moved. We use the method of simulated maximum likelihood (SML) to estimate the heterogeneity by using the specification of random effects wit...

The lack of access to formal credit at affordable cost (effective interest) is the most critical constraint faced by the rural entrepreneurs to get involved in productive profitable business activities. This study explores the causes behind the widespread existence of informal credits as investment capital for small house-based business. Based on a primary survey on house based industrial owner...

The study aims to detect demographics and economic factors the related residential properties social-environmental indicators affecting household savings in Turkey. In study, cross-sectional data was obtained from Household Budget Survey conducted by Turkish Statistical Institute between years 2015-2017. Binary logistic regression binary probit analyses determined factors. According analysis re...

We propose a new adaptive procedure for dose-finding in clinical trials with combination of two drugs when both efficacy and toxicity responses are available. We model the distribution of this bivariate binary endpoint using the bivariate probit model. The analytic formulae for the Fisher information matrix are obtained, that form the basis for derivation of the locally optimal, minimax, Bayesi...

Abstract: Most common regression models for analyzing binary random variables are logistic and probit regression models. However it is well known that the estimates of regression coefficients for these models are not robust to outliers [26]. The robit regression model [1, 16] is a robust alternative to the probit and logistic models. The robit model is obtained by replacing the normal (logistic...

When the outcome is binary, psychologists often use nonlinear modeling strategies such as logit or probit. These are neither optimal nor justified when objective to estimate causal effects of experimental treatments. Researchers need take extra steps convert and probit coefficients into interpretable quantities, they do, these quantities remain difficult understand. Odds ratios, for instance, d...