In this paper, we examine the problem of estimating the sensitive characteristics and behaviors in a multinomial randomized response model using Bayesian approach. We derived a posterior distribution for parameter of interest for multinomial randomized response model. Based on the posterior distribution, we also calculated a credible intervals and mean squared error (MSE). We finally compare th...

Estimation of disaggregate mode choice models to estimate the ridership share on a proposed new (or improved) intercity travel service and to identify the modes from which existing intercity travelers will be diverted to the new or upgraded service constitutes a critical part of evaluating alternative travel service proposals to alleviate intercity travel congestion. This paper develops a new h...

this study examined the nature and patterns of rice consumption in nigeria, using kwara state as a case study. the study methodology comprised a two stage sampling technique which was used to survey 110 rice consumer households across two villages and six towns in kwara state. analytical tools used in the study include descriptive statistics and the multinomial logit model. the major factors th...

Categorical data frequently arise in applications in the social sciences. In such applications,the class of log-linear models, based on either a Poisson or (product) multinomial response distribution, is a flexible model class for inference and prediction. In this paper we consider the Bayesian analysis of both Poisson and multinomial log-linear models. It is often convenient to model multinomi...

MARKET RESPONSE MEASUREMENT USING THE MULTINOMIAL, MULTIATTRIBUTE LOGIT CHOICE MODEL by Peter Manning Guadagni Submitted to the Alfred P. Sloan School of Management on May 15, 1980, in partial fulfillment of the requirements for the degree of Master of Science. Universal Product Code (UPC) scanning is the key to a new marketing data source. Unfortunately, most existing marketing models do not h...

In certain statistical process control applications, quality of a process or product can be characterized by a function commonly referred to as profile. Some of the potential applications of profile monitoring are cases where quality characteristic of interest is modelled using binary,multinomial or ordinal variables. In this paper, profiles with multinomial response are studied. For this purpo...

This article introduces a Markov chain Monte Carlo (MCMC) method for sampling the parameters of a multinomial logit model from their posterior distribution. Let yi ∈ {0, . . . ,M} denote the categorical response of subject i with covariates xi = (xi1, . . . , xip) T . Let X = (x1, . . . ,xn) T denote the design matrix, and let y = (y1, . . . , yn) T . Multinomial logit models relate yi to xi th...

We explore inference on regression coefficients in semiparametric multinomial response models. consider cross?sectional, and both static dynamic panel settings where we focus throughout under sufficient conditions for point identification. The approach to identification uses a matching insight all three models coupled with variation regressors: cross?section data, match across individuals while...

©FSRH J Fam Plann Reprod Health Care 2008: 34(3) What is it? When a response variable has only two possible values (e.g. recurrence/not), binary logistic regression is commonly used to test or model the association between that response and a number of potential explanatory variables, with each association estimated in terms of an odds ratio (OR). Multinomial logistic regression is an extension...