INTRODUCTION In 2006, the Association of American Medical Colleges (AAMC) issued a recommendation that medical schools increase the supply of physicians by 30% to meet the patient needs of the new millennium. OBJECTIVE To provide financial analysis of the cost of increasing class size. METHODS To determine the financial consequences of increasing medical student enrollment and in the absenc...

This study integrates association rules analysis, a methodology for selecting potential interactions, with Poisson regression modeling. Though typically ignored in conventional Poisson regression, interactions are very common in practice. However, selecting a Poisson regression model when many main effects and interactions are involved is problematic. In this study, we develop a model selection...

background: controlled ovarian hyperstimulation (coh) in conjunction with intrauterine inseminations (iui) are commonly used to treat infertile couples. in this study we evaluated the relationship between iui outcome and special causes of infertility. we also aimed to examine parameters that might predict success following iui. materials and methods: in this cross-sectional study, we included 9...

Whole exome and whole genome sequencing are likely to be potent tools in the study of common diseases and complex traits. Despite this promise, some very difficult issues in data management and statistical analysis must be squarely faced. The number of rare variants identified by sequencing is apt to be much larger than the number of common variants encountered in current association studies. T...

This paper describes geographically weighted Poisson regression (GWPR) and its semi-parametric variant as a new statistical tool for analysing disease maps arising from spatially non-stationary processes. The method is a type of conditional kernel regression which uses a spatial weighting function to estimate spatial variations in Poisson regression parameters. It enables us to draw surfaces of...

The focus of this study is on statistical analysis of categorical responses, where the response values are dependent of each other. The most typical example of this kind of dependence is when repeated responses have been obtained from the same study unit. For example, in Paper I, the response of interest is the pneumococcal nasopharengyal carriage (yes/no) on 329 children. For each child, the c...

Universal coefficients of determination are investigated which quantify the strength of the relation between a vector of dependent variables Y and a vector of independent covariates X. They are defined as measures of dependence between Y andX through θ(x), with θ(x) parameterizing the conditional distribution of Y given X = x. If θ(x) involves unknown coefficients γ the definition is conditiona...

Universal coefficients of determination are investigated which quantify the strength of the relation between a vector of dependent variables Y and a vector of independent covariates X. They are defined as measures of dependence between Y and X through θ(x), with θ(x) parameterizing the conditional distribution of Y given X = x. If θ(x) involves unknown coefficients γ the definition is condition...

Functional linear regression models are effectively used in gene-based association analysis of complex traits. These models combine information about individual genetic variants, taking into account their positions and reducing the influence of noise and/or observation errors. To increase the power of methods, where several differently informative components are combined, weights are introduced...

Clustered data arise commonly in practice and it is often of interest to estimate the mean response parameters as well as the association parameters. However, most research has been directed to inference about the mean response parameters with the association parameters relegated to a nuisance role. There is little work concerning both the marginal and association structures, especially in the ...