Randomized response and the binary probit model

Randomized response and the binary probit model

The Analysis of Bayesian Probit Regression of Binary and Polychotomous Response Data

The goal of this study is to introduce a statistical method regarding the analysis of specific latent data for regression analysis of the discrete data and to build a relation between a probit regression model (related to the discrete response) and normal linear regression model (related to the latent data of continuous response). This method provides precise inferences on binary and multinomia...

A Binary-Ordered Probit Model of Cigarette Demand

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...

A Two-stage Binary Optional Randomized Response Model

Social Desirability Bias (SDB) is the tendency in respondents to answer questions untruthfully in the hope of giving good impression to others. SDB occurs when the survey question is highly sensitive or personal, and responses cause sample statistics to systematically over-or underestimate corresponding population parameters. The Randomized Response Technique (RRT) is one of several methods to ...

Multivariate Probit Analysis of Binary Time

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 Fitzmaur...