Logistic regression is a statistical method used to examine the relationship between a binary outcome variable and one or more explanatory variables. It is a special case of a regression model that ...

For example, logistic regression is commonly used to predict whether or not customers will default on their loans as a measure of creditworthiness. How Logistic Regression Works ...

Results of the fast elimination analysis are shown in Output 39.1.9 and Output 39.1.10. Initially, a full model containing all six risk factors is fit to the data (Output 39.1.9). In the next step ...

This book also explains the differences and similarities between the many generalizations of the logistic regression model. The following topics are covered: binary logit analysis, logit analysis of ...

This is problematic because an odds ratio always overestimates the risk ratio, and this overestimation becomes larger with increasing incidence of the outcome. 5 There are alternatives for logistic ...

Rosineide F. da Paz, Narayanaswamy Balakrishnan, Jorge Luis Bazán, L-Logistic regression models, Brazilian Journal of Probability and Statistics, Vol. 33, No. 3 (2019), pp. 455-479 ...

With the rapid development of the global economy, many countries particularly China are facing significant aging challenges [ ...