The co-twin control design has been widely used in studying the effects of environmental factors on the development of diseases. For binary outcomes that arise from co-twin control studies, the conditional likelihood method is commonly used. This approach, however, does not readily extend to ordinal response data because the standard conditional likelihood does not exist for cumulative logit or...

We study generalized linear models for time series of counts, where serial dependence is introduced through a dependent latent process in the link function. Conditional on the covariates and the latent process, the observation is modelled by a negative binomial distribution. To estimate the regression coefficients, we maximize the pseudolikelihood that is based on a generalized linear model wit...

We examine several approaches for inferring logit models from empirical margins of predictor covariates and conditional margins containing the means of a binary response for each covariate margin. One method is to fit proxy data to the conditional response using the beta distribution, a process we call “margin analysis.” Proxy data can obtained using three approaches: (1) implementing the itera...

The article analyses the question whether women and men differ in their tastes for location factors. The question is answered by quantifying the impact of location characteristics on interregional migration flows across Germany. The analysis is based on a grouped conditional logit approach. We augment the framework by controlling for violation of the independence of irrelevant alternatives assu...

The aim of this research is to evaluate future retail developments in a medium-sized town and the indirect effects of individual behaviour on the local economy. Therefore we combine a spatial microsimulation model with a conditional logit model estimating the spatial shopping behaviour of households to simulate the effect of future retail developments. Then, we estimate the macro effects of the...

This paper estimates the links between middle-income trap and women’s employment with dataset of 27 countries for 22 years. In line study’s prime objective, a panel logit regression model is used. The findings based on conditional fixed-effects logistic show that possibility country being high-income economy significantly associated rate, productivity, innovation, institution. results also fema...

We explore the extent to which the decisions of participants in a speculative market effectively account for information contained in prices and price movements. The horserace betting market is chosen as an ideal environment to explore these issues. A conditional logit model is constructed to determine winning probabilities based on bookmakers’ closing prices and the time indexed movement of pr...

The package support.CEs provides seven basic functions that support the implementation of choice experiments (CEs) in R: two functions for creating a CE design, which is based on orthogonal main-effect arrays; a function for converting a CE design into questionnaire format; a function for converting a CE design into a design matrix; a function for making the data set suitable for the implementa...

We use a Markov Chain Monte Carlo (MCMC) MML algorithm to learn hybrid Bayesian networks from observational data. Hybrid networks represent local structure, using conditional probability tables (CPT), logit models, decision trees or hybrid models, i.e., combinations of the three. We compare this method with alternative local structure learning algorithms using the MDL and BDe metrics. Results a...

The paper is concerned with the role of international outsourcing and import penetration for determining individual perceived job security. Combining industry-level outsourcing and trade measures with micro-level data from a large household panel survey, we estimate a number of conditional logit models accounting for the ordinal nature of reported job loss fears and individual unobserved hetero...