Logistic regression was used to develop a risk prediction model using the FIT result and screening data: age, sex and previous screening history.

A supremum-type statistic, based on partial sums of residuals, is proposed to test the validity of the mean function of the response variable in a generalized linear model. The proposed test does not ...

Logistic regression is a widely applied tool for the analysis of binary response variables. Several test statistics have been proposed for the purpose of assessing the goodness of fit of the logistic ...

A multivariable logistic regression model was used to find associations with an unsatisfactory FIT and any follow-up testing after the unsatisfactory FIT was submitted.

Scikit-learn was used to fit logistic regression models, and a train/test split was created on the data, with test data only used for evaluating the performance of the models.

The demo program loads a 200-item set training data, and a 40-item set of test data into memory. Next, the demo creates and trains a logistic regression model using the LogisticRegression class from ...

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 ...