The Log-gamma-logistic Regression Model: Estimation, Sensibility and Residual Analysis

Bayesian and Iterative Maximum Likelihood Estimation of the Coefficients in Logistic Regression Analysis with Linked Data

This paper considers logistic regression analysis with linked data. It is shown that, in logistic regression analysis with linked data, a finite mixture of Bernoulli distributions can be used for modeling the response variables. We proposed an iterative maximum likelihood estimator for the regression coefficients that takes the matching probabilities into account. Next, the Bayesian counterpart...

"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

Log-New Weibull Extension Regression Models: Sensitivity and Residual Analysis

Standard lifetime distributions usually very place strong restrictions on the data as is well illustrated by their inability to produce bathtub curves, and thus to adequately interpret data with this character. Mudholkar et al. (1995) introduced the exponentiated-Weibull distribution and Xie et al. (2002) proposed the new Weibull extension distribution. The new Weibull extension distribution wi...

Multiple Logistic Regression and Model Fit Multiple Logistic Regression Just as in OLS regression, logistic models

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...