caesarean section (c-section) rates have been increasing dramatically in the past decades around the world. this increase has been attributed to multiple factors such as maternal, socio-demographic and institutional fac-tors. therefore, this study examines the impact of maternal, socio-demographic and relevant characteristics on caesar-ean delivery in the northern region of bangladesh.this stud...

Multiple Logistic Regression Just as in OLS regression, logistic models can include more than one predictor. The analysis options are similar to regression. One can choose to select variables, as with a stepwise procedure, or one can enter the predictors simultaneously, or they can be entered in blocks. Variations of the likelihood ratio test can be conducted in which the chi-square test (G) is...

the bankruptcy prediction models have long been proposedas a key subject in finance. the present study, therefore, makes aneffort to examine the corporate bankruptcy prediction through employmentof the genetic algorithm model. furthermore, it attempts to evaluatethe strategies to overcome the drawbacks of ordinary methods forbankruptcy prediction through application of genetic algorithms. thesa...

logistic regression models are frequently used in clinicalresearch and particularly for modeling disease status and patientsurvival. in practice, clinical studies have several limitationsfor instance, in the study of rare diseases or due ethical considerations, we can only have small sample sizes. in addition, the lack of suitable andadvanced measuring instruments lead to non-precise observatio...

In medical research, there is great interest in developing methods for combining biomarkers. We argue that selection of markers should also be considered in the process. Traditional model/variable selection procedures ignore the underlying uncertainty after model selection. In this work, we propose a novel model-combining algorithm for classification in biomarker studies. It works by considerin...