JSTOR Daily

Minimum Distance Estimation for the Logistic Regression Model

It is well known that the maximum likelihood fit of the logistic regression parameters can be greatly affected by atypical observations. Several robust alternatives have been proposed. However, if we ...
JSTOR Daily

Estimation and Inference for Logistic Regression with Covariate Misclassification and Measurement Error in Main Study/Validation Study Designs

In epidemiological studies, continuous covariates often are measured with error and categorical covariates often are misclassified. Using the logistic regression ...
The Lancet

Effective sample size for individual risk predictions: quantifying uncertainty in machine learning models

Individual prediction uncertainty is a key aspect of clinical prediction model performance; however, standard performance metrics do not capture it. Consequently, a model might offer sufficient ...
Risk

Calibration alternatives to logistic regression and their potential for transferring the statistical dispersion of discriminatory power into uncertainties in probabilities of ...

The transformation of credit scores into probabilities of default plays an important role in credit risk estimation. The linear logistic regression has developed into a standard calibration approach ...
technologynetworks

Logistic Regression

Logistic regression is a powerful statistical method that is used to model the probability that a set of explanatory (independent or predictor) variables predict data in an outcome (dependent or ...
Nature

A unifying framework for robust association testing, estimation, and genetic model selection using the generalized linear model

Genome-wide association studies (GWAS) are widely used to uncover novel genetic susceptibility loci for complex genetic diseases. If the true genetic model is known, the association test reflecting ...
Risk

Loss given default estimation: a two-stage model with classification tree-based boosting and support vector logistic regression

The Basel Accords allow banks to estimate credit risk. Accordingly, more attention has been dedicated recently to the analysis of loss given default (LGD) and the development of an LGD estimation ...
Simon Fraser University

Generalized Estimating Equations

X ij = [x ij1, ... , x ijp]' The Generalized Estimating Equation of Liang and Zeger (1986) for estimating the p ×1 vector of regression parameters is an extension of the independence estimating ...