Standard curves from 150 determinations of 10 different hormone radioimmunoassays have been evaluated using the following four procedures: logit transformation as performed by Rodbard, Healy's 4-component-logit, spline approximation and a linear interpolation program. The results, calculated by computer, have been compared with manual analysis as the refernce method. The influece of various cor...

The most persistently troubling empirical result in the contingent valuation method literature is the tendency for hypothetical willingness to pay to overestimate real willingness to pay. We suggest a new approach to test and correct for hypothetical bias using a latent choice multinomial logit (LCMNL) model. To develop this model, we extend Dempster, Laird, and Rubin’s (1977) work on the EM al...

Popular information systems such as community-based question answering sites (CQAs) and electronic networks of practice (ENPs) rely on accurate assessment of user contributed contents to ensure effective knowledge creation and exchange. We study the issue of content quality assessment through a context-free linguistic analysis, and hypothesize that, based on psycholinguistic theories and the po...

Despite the vital role of the utility function in welfare measurement, the implications of working with incorrect utility specifications have been largely neglected in the choice experiments literature. This paper addresses the importance of specification with a special emphasis on the effects of mistaken assumptions about the marginal utility of income. Monte Carlo experiments were conducted u...

The nested logit model has been used extensively to model multi-dimensional choice situations. A drawback of the nested logit model is that it does not allow choice alternatives to share common unobserved attributes along all the dimensions characterizing the multi-dimensional choice context. This paper formulates a mixed multinomial logit structure that accommodates unobserved correlation acro...

When design decisions are informed by consumer choice models, uncertainty in the choice model and its share predictions creates uncertainty for the designer. We take a first step in investigating the variation in and accuracy of market share predictions by characterizing fit and forecast accuracy of multinomial logit, mixed logit, and nested logit models over a variety of utility function speci...

Binary data are widely used for spatial modeling and when inferences and predictions are to be derived. If a Generalized Linear Model (GLM) is applied, logit functions are often used. Here we show alternatives to the traditional logit approach using probit and the complementary log log link functions. We present a software-based approach and two methods of assessing which link function performs...

Categorical outcome (or discrete outcome or qualitative response) regression models are models for a discrete dependent variable recording in which of two or more categories an outcome of interest lies. For binary data (two categories) probit and logit models or semiparametric methods are used. For multinomial data (more than two categories) that are unordered, common models are multinomial and...