The HICS Physiology blog

                                                                                                Survival analysis encompasses a family of statistical methods used to study time‑to‑event outcomes, where the event may be death, relapse, ICU discharge, mechanical ventilation weaning, or any clinically meaningful endpoint. What distinguishes survival data from ordinary continuous outcomes is censoring—patients may be lost to follow‑up or may not have experienced the event by the end of the study. Survival analysis methods explicitly account for this incomplete information, making them indispensable in clinical research, oncology, critical care, and epidemiology. 1. Kaplan–Meier Estimator The Kaplan–Meier (KM) method is the foundational non‑parametric tool...

                                                                                                         Educational Note: Regression Analysis in Medical Statistics Regression analysis is a cornerstone of medical statistics, enabling researchers to explore and quantify relationships between variables. It helps determine how one or more independent variables (such as age, BMI, or blood pressure) influence a dependent variable (such as disease outcome, blood glucose level, or survival time). This method is vital for identifying risk factors, predicting outcomes, and evaluating treatment effects. Types of Regression Models Linear Regression: Examines continuous outcomes. For example, how systolic blood pressure changes with...

                                                                                                           Tests of Correlation Correlation analysis is a cornerstone of medical statistics, used to quantify the strength and direction of association between two variables. In clinical research, it helps investigators understand whether changes in one biological, physiological, or behavioral measure are associated with changes in another. Correlation does not imply causation, but it provides essential groundwork for hypothesis generation, risk factor identification, and model building. This write‑up provides a comprehensive overview of the major tests of correlation used in medical statistics, their assumptions, interpr...