Many researchers have used the conditional logit model to examine migration. One common objection to this model is that it carries the independence from irrelevant alternatives (IIA) assumption, which may be too restrictive. This study compares the conditional logit with models that partially relax (nested logit) or fully relax (mixed logit) the IIA assumption. We will begin to learn whether as...

OBJECTIVES To explain the use of interaction terms in nonlinear models. STUDY DESIGN We discuss the motivation for including interaction terms in multivariate analyses. We then explain how the straightforward interpretation of interaction terms in linear models changes in nonlinear models, using graphs and equations. We extend the basic results from logit and probit to difference-in-differenc...

Summary This paper introduces a new data-driven methodology for estimating sparse covariance matrices of the random coefficients in logit mixture models. Researchers typically specify models under one two extreme assumptions: either an unrestricted full matrix (allowing correlations between all coefficients), or restricted diagonal no at all). Our objective is to find optimal subsets correlated...

a method based on the genetic algorithm (ga) was developed to study the phase behavior of multicomponent and multiphase systems. upon application of the ga to the thermodynamic models which are commonly used to study the vle, vlle and lle phase equilibria, the physically meaningful values for the binary interaction parameters (bip) of the models were obtained. using the method proposed in this ...

A fast and simple method is proposed that produces approximate multivariate local D-optimal designs of high e¢ ciency for models with binary response. The method assumes availability of a D-optimal design for a parallel normal response linear problem that has the same linear predictor, with an assumption of homogenous variance; the change required to transform the standard design into an e¢ cie...