Immigrant retention in NB: an analysis using administrative Medicare Registry data

Journal of Population Research - This paper examines immigrant retention using a novel approach based on data contained in New Brunswick’s Medicare Registry database. To date, researchers...     

Informal mentoring and young adult employment

This study explores the role of informal mentoring (i.e., developing an important relationship with a non-parental adult) in the transition to full time employment among young adults (age 23–28). Multivariate analysis of the Add Health data reveals that mentoring is positively related to the likelihood of full time employment, and the relationship involves both selection and causation processes. Entrance into the world of work facilitates the development of mentoring relationships, especially among youth who identify work-related mentors after adolescence. These relationships have the potential for promoting attachment to the labor force. Mentoring relationships that develop outside of work settings and during adolescence have a positive impact on the odds of full time employment. The receipt of guidance and advice from mentors, as well as access to weak-tied mentoring relationships, teacher mentors, and friend mentors all contribute to the increased odds of employment in young adulthood. However, adolescent mentoring may be less effective among young women than it is among young men.     

State-of-the-Art Developments in Expert Systems and Strategic Marketing Planning

This paper describes a case history of the development of an Expert System in Strategic Marketing Planning codenamed EXMAR. It traces the evolution of the system from the formation of the DTI club two years ago to the launch of the prototype model. The paper outlines the technical and domain–specific obstacles encountered en route and how these were overcome. A number of conclusions are drawn from the project. The principal one is that there is a bright future for expert systems in the field of strategic management. Professor Malcolm McDonald is the principal expert to the club. Hugh Wilson is a senior consultant with Artificial Intelligence Ltd. He was also the knowledge engineer and the project manager. For readers who would like a simple explanation of Expert Systems, please refer to Professor McDonald's paper ‘Marketing Planning and Expert Systems: an Epistemology of Practice’, Marketing Intelligence and Planning, 7, 7/8, 1989.     

Alternative beta estimation for the market model using partially adaptive techniques

The leptokurtosls of many security market return distributions can contaminate ordinary least squares estimates of the β coefficient of the market model. Partially adaptive estimation techniques accommodate the possibility of fat tailed distributions. this methodology limits the influence of extremely large residuals and yields estimates which are both statistically and practically different from ordinary least squares.     

Markov chain Monte Carlo exact inference for binomial and multinomial logistic regression models

We develop Metropolis-Hastings algorithms for exact conditional inference, including goodness-of-fit tests, confidence intervals and residual analysis, for binomial and multinomial logistic regression models. We present examples where the exact results, obtained by enumeration, are available for comparison. We also present examples where Monte Carlo methods provide the only feasible approach for exact inference.     

Mixture modelling of recurrent event times with long-term survivors: Analysis of Hutterite birth intervals

We propose a mixture model that combines a discrete-time survival model for analyzing the correlated times between recurrent events, e.g. births, with a logistic regression model for the probability of never experiencing the event of interest, i.e., being a long-term survivor. The proposed survival model incorporates both observed and unobserved heterogeneity in the probability of experiencing the event of interest. We use Gibbs sampling for the fitting of such mixture models, which leads to a computationally intensive solution to the problem of fitting survival models for multiple event time data with long-term survivors. We illustrate our Bayesian approach through an analysis of Hutterite birth histories.     

Markov chain Monte Carlo exact inference for social networks

The uniformly most powerful unbiased test of reciprocity compares the observed number of mutual relations to its exact conditional distribution. Metropolis–Hastings algorithms have been proposed for generating from this distribution in order to perform Monte Carlo exact inference. Triad census statistics are often used to test for the presence of network group structure. We show how one of the proposed Metropolis–Hastings algorithms can be modified to generate from the conditional distribution of the triad census given the in-degrees, the out-degrees and the number of mutual dyads. We compare the results of this algorithm with those obtained by using various approximations.