On the correspondence from Bayesian log-linear modelling to logistic regression modelling with gg-priors

Consider a set of categorical variables where at least one of them is binary. The log-linear model that describes the counts in the resulting contingency table implies a specific logistic regression model, with the binary variable as the outcome. Within the Bayesian framework, the $g$-prior and mixtures of $g$-priors are commonly assigned to the parameters of a generalized linear model. We prove that assigning a $g$-prior (or a mixture of $g$-priors) to the parameters of a certain log-linear model designates a $g$-prior (or a mixture of $g$-priors) on the parameters of the corresponding logistic regression. By deriving an asymptotic result, and with numerical illustrations, we demonstrate that when a $g$-prior is adopted, this correspondence extends to the posterior distribution of the model parameters. Thus, it is valid to translate inferences from fitting a log-linear model to inferences within the logistic regression framework, with regard to the presence of main effects and interaction terms.Comment: 27 page

Eating Disorders in Sport : a call for methodological diversity

From the emergence of isolated studies in the early 1980s to the concentrated and burgeoning research base of the present day, scholars within sport psychology have been motivated to address the problem of eating disorders in sport. Heavily influenced by the medical model of scientific inquiry, the extant literature offers important insights into prevalence and aetiology. Despite this progress, there is much that is poorly understood about athlete eating disorders and existing approaches are vulnerable to considerable critique. This paper highlights some of the fundamental problems with the medical model and argues that its current dominance has created an overly narrow knowledge base. It is proposed that an increase in qualitative, interpretive accounts, that prioritize the subjectivity of experience over the serialization of symptoms, is necessary if we are to achieve a balanced and more complete understanding of eating disorders in sport

The 'population' variable in urban design and regional planning (the case of Greece)

The population distribution in the Greek region shows strong spatial disparities. The depopulation of entire areas, coupled with the excessive population growth of the two largest cities (Athens and Thessaloniki) as well as the intense spatial disparities within the cities are significant challenges in managing our country; the main instrument to achieve this management is spatial planning. At the same time, the population is a variable which comprises a deciding factor in the procedure of spatial planning. Exploring the characteristics of the population of a region and predicting the evolution is not an end in itself for analysis, their usefulness, however, lies on the fact that part of the characteristics of urban space is determined by size, demographic and social characteristics of the population concentrated in this space. The purpose of this work is to study how the population variable is included in spatial planning. In order to answer to the above question we will study the technical specifications of the Greek plans trying to understand and specify which characteristics of the population are considered in the design and how. Also, if there are differences between the two main stages of spatial planning (analysis phase, final proposal phase) in relation to the population study. We will study 4 specific cases of randomly chosen masterplans (the corresponding plans of the Greek legislation) in order to try to verify the early feedback which will come up. The conclusions are interesting and highlight some of the weaknesses and shortcomings of the Greek plans and the Greek system of design. Finally, some suggestions are presented which we believe they can improve the current weaknesses

A semi-parametric approach to estimate risk functions associated with multi-dimensional exposure profiles: application to smoking and lung cancer

A common characteristic of environmental epidemiology is the multi-dimensional aspect of exposure patterns, frequently reduced to a cumulative exposure for simplicity of analysis. By adopting a flexible Bayesian clustering approach, we explore the risk function linking exposure history to disease. This approach is applied here to study the relationship between different smoking characteristics and lung cancer in the framework of a population based case control study

Automated Selection of Hotspots (ASH): enhanced automated segmentation and adaptive step finding for Ki67 hotspot detection in adrenal cortical cancer

BACKGROUND: In prognosis and therapeutics of adrenal cortical carcinoma (ACC), the selection of the most active areas in proliferative rate (hotspots) within a slide and objective quantification of immunohistochemical Ki67 Labelling Index (LI) are of critical importa

On synthetic interval data with predetermined subject partitioning and partial control of the variables’ marginal correlation structure

A standard approach for assessing the performance of partition models is to create synthetic datasets with a prespecified clustering structure and assess how well the model reveals this structure. A common format involves subjects being assigned to different clusters, with observations simulated so that subjects within the same cluster have similar profiles, allowing for some variability. In this manuscript, we consider observations from interval variables. Interval data are commonly observed in cohort and Genome-Wide Association studies, and our focus is on Single-Nucleotide Polymorphisms. Theoretical and empirical results are utilized to explore the dependence structure between the variables in relation to the clustering structure for the subjects. A novel algorithm is proposed that allows control over the marginal stratified correlation structure of the variables, specifying exact correlation values within groups of variables. Practical examples are shown, and a synthetic dataset is compared to a real one, to demonstrate similarities and differences.Peer reviewe

Succinate dehydrogenase (SDH)-deficient renal carcinoma:a morphologically distinct entity: a clinicopathologic series of 36 tumors from 27 patients

Succinate dehydrogenase (SDH)-deficient renal carcinoma has been accepted as a provisional entity in the 2013 International Society of Urological Pathology Vancouver Classification. To further define its morphologic and clinical features, we studied a multi-institutional cohort of 36 SDH-deficient renal carcinomas from 27 patients, including 21 previously unreported cases. We estimate that 0.05% to 0.2% of all renal carcinomas are SDH deficient. Mean patient age at presentation was 37 years (range, 14 to 76 y), with a slight male predominance (M:F=1.7:1). Bilateral tumors were observed in 26% of patients. Thirty-four (94%) tumors demonstrated the previously reported morphology at least focally, which included: solid or focally cystic growth, uniform cytology with eosinophilic flocculent cytoplasm, intracytoplasmic vacuolations and inclusions, and round to oval low-grade nuclei. All 17 patients who underwent genetic testing for mutation in the SDH subunits demonstrated germline mutations (16 in SDHB and 1 in SDHC). Nine of 27 (33%) patients developed metastatic disease, 2 of them after prolonged follow-up (5.5 and 30 y). Seven of 10 patients (70%) with high-grade nuclei metastasized as did all 4 patients with coagulative necrosis. Two of 17 (12%) patients with low-grade nuclei metastasized, and both had unbiopsied contralateral tumors, which may have been the origin of the metastatic disease. In conclusion, SDH-deficient renal carcinoma is a rare and unique type of renal carcinoma, exhibiting stereotypical morphologic features in the great majority of cases and showing a strong relationship with SDH germline mutation. Although this tumor may undergo dedifferentiation and metastasize, sometimes after a prolonged delay, metastatic disease is rare in the absence of high-grade nuclear atypia or coagulative necrosis