background and aims: diabetes type ii (non-insulin dependent) which is one of the most prevalent diabetes types in the world emerges in people with the age of above 55 and genetic and environmental factors interfere in this disease. the aim of this study was to determine the factors affecting diabetes type ii with generalized mixed linear model. methods: population of this study included 2820 p...

background: venous diseases including varicose veins and chronic venous insufficiency are one of the most important pathogenic factors worldwide. high prevalence of varicose veins and its complications is an emerging problem in the twenty-first century. this study aimed to determine the prevalence and associated risk factors of varicose veins in female hairdressers in shahroud, north of iran in...

background: liver cancer mortality is high in thailand but utility of related vital statistics is limited due to national vital registration (vr) data being under reported for specific causes of deaths. accurate methodologies and reliable supplementary data are needed to provide worthy national vital statistics. this study aimed to model liver cancer deaths based on verbal autopsy (va) study in...

various statistical methods have been proposed in terms of predicting the outcomes of facing special factors. in the classical approaches,  making the probability distribution or known probability density functions is ordinarily necessary to predict the desired outcome. however, most of the times enough information about the probability distribution of studied variables is not available to the ...

This paper proposes a distributionally robust approach to logistic regression. We use the Wasserstein distance to construct a ball in the space of probability distributions centered at the uniform distribution on the training samples. If the radius of this ball is chosen judiciously, we can guarantee that it contains the unknown datagenerating distribution with high confidence. We then formulat...

This chapter describes a tree-structured extension and generalization of the logistic regression method for fitting models to a binary-valued response variable. The technique overcomes a significant disadvantage of logistic regression, which is interpretability of the model in the face of multicollinearity and Simpson’s paradox. Section 1 summarizes the statistical theory underlying the logisti...

This paper addresses the important tradeoff between privacy and learnability, when designing algorithms for learning from private databases. We focus on privacy-preserving logistic regression. First we apply an idea of Dwork et al. [6] to design a privacy-preserving logistic regression algorithm. This involves bounding the sensitivity of regularized logistic regression, and perturbing the learn...