Linear and logistic regression analysis

"Secure" Log-Linear and Logistic Regression Analysis of Distributed Databases

The machine learning community has focused on confidentiality problems associated with statistical analyses that “integrate” data stored in multiple, distributed databases where there are barriers to simply integrating the databases. This paper discusses various techniques which can be used to perform statistical analysis for categorical data, especially in the form of log-linear analysis and l...

Log - Linear Modeling and Logistic Regression

Study Applicable for Multi-Linear Regression Analysis and Logistic Regression Analysis

Current study focus on using method of multi-linear regression analysis and logistic regression analysis, and discuss about the condition and scope of multi-linear regression analysis and logistic regression analysis. A modeling method has been introduced keeping in the basic principles of multi-linear regression analysis and logistic regression analysis. The modeling method and two forms of an...

Logistic Regression Tree Analysis

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...

Understanding logistic regression analysis

Logistic regression is used to obtain odds ratio in the presence of more than one explanatory variable. The procedure is quite similar to multiple linear regression, with the exception that the response variable is binomial. The result is the impact of each variable on the odds ratio of the observed event of interest. The main advantage is to avoid confounding effects by analyzing the associati...