This study aims to determine the relationship between students’ excitement toward studying statistics and their attitude using ordinal logistic regression.

This study examines whether different drug types influence fracture risk among patients. Poisson regression is used to model fracture counts and estimate incidence rate ratios.

A Logistic Regression Approach is used to investigate which physiological and demographic variables significantly influence diabetes status.

In this study, a conditional logistic regression model was employed to explore the relationship between selected clinical and behavioral predictors—smoking status, systolic blood pressure (SBP), and electrocardiogram (ECG) abnormalities—and the likelihood of myocardial infarction.

This cross-sectional analysis explores how demographic and behavioral variables influence knowledge levels, perceptions, and attitudes towards participation in COVID-19 clinical trials.

This clinical trial aims to evaluate the safety profiles of two drugs by comparing their impact on key vital-sign-related adverse events.

The goal of this study is to evaluate whether self-esteem levels of participants change significantly over three different time points (pre-test, mid-test, and post-test).