validation is an important enterprise especially when a test is a high stakes one. demographic variables like gender and field of study can affect test results and interpretations. differential item functioning (dif) is a way to make sure that a test does not favor one group of test takers over the others. this study investigated dif in terms of gender in the reading comprehension subtest (35 i...

Due to the low information content of individual SAR images, single-band SAR data do not provide highly accurate land cover classification. However, in areas under risk where rapid land cover mapping is required, the advantages of SAR which include cloud penetration and day/night acquisition, are evident in comparison to optical data. The main research goal of this study is to fuse different fr...

Based on logistic regression (LR) and artificial neural network (ANN) methods, we construct an LR model, an ANN model and three types of a two-stage hybrid model. The two-stage hybrid model is integrated by the LR and ANN approaches. We predict the credit risk of China’s small and medium-sized enterprises (SMEs) for financial institutions (FIs) in the supply chain financing (SCF) by applying th...

In this paper, we extend the traditional logistic regression model(LR) to the bounded logistic regression model(BLR) and compare them. We also derive the update rules of both model using stochastic gradient desent(SGD). The effects of choosing different learning rate schedule, stopping conditions, parameters initialization and learning algorithm settings are also discussed. We get the accuracy ...

With recent advances in biotechnology, genome-wide association study (GWAS) has been widely used to identify genetic variants that underlie human complex diseases and traits. In case-control GWAS, typical statistical strategy is traditional logistical regression (LR) based on single-locus analysis. However, such a single-locus analysis leads to the well-known multiplicity problem, with a risk o...

PURPOSE The purpose of this article is twofold: 1) introducing logistic regression (LR), a multivariable method for modeling the relationship between multiple independent variables and a categorical dependent variable, and 2) examining use and reporting of LR in the nursing literature. METHODS Text books on LR and research articles employing LR as main statistical analysis were reviewed. Twen...

This paper compares, for a microfinance institution, the performance of two individual classification models: Logistic Regression (Logit) and Multi-Layer Perceptron Neural Network (MLP), to evaluate the credit risk problem and discriminate good creditors from bad ones. Credit scoring systems are currently in common use by numerous financial institutions worldwide. However, credit scoring using ...

Logistic regression (LR) is a widely used multivariable method for modeling dichotomous outcomes. This article examines use and reporting of LR in the medical literature by comprehensively assessing its use in a selected area of medical study. Medline, followed by bibliography searches, identified 15 peer-reviewed English-language articles with original data, employing LR, published between 198...

In this paper we propose a simple tensor-based approach to temporal features modeling that is applicable as means for logistic regression (LR) enhancement. We evaluate experimentally the performance of an LR system based on the proposed model in the ClickThrough Rate (CTR) estimation scenario involving processing of very large multi-attribute data streams. We compare our approach to the existin...