We propose in this paper a free-knot spline framework for conducting piecewise linear logistic regression ... A study of simulated mortality outcomes conditioned on measured body mass index (BMI, kg/m ...

The analytical process includes exploratory data analysis, preprocessing steps such as handling missing values and outliers, feature selection, and model evaluation using metrics like R², MAE, and ...

and predictors of in-hospital mortality were analyzed using multivariable logistic regression. Results: We included 9,939 unique CICU patients with available data for SI. The mean age was 69 years old ...

In this study, we compare the performance of Logistic Regression and Decision Trees in predicting mortality risk among patients diagnosed with heart failure. The data for this analysis was sourced ...

Ordinary linear regression ... Categorical data analysis, including contingency table analysis, measures of association, tests of independence, tests of symmetry. How to use R to fit GLMs using real ...