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Evidence-Based Medicine

Regression Analysis Explained: Confounders & Clinical Meaning

Regression analysis explained to identify confounders and predict clinical outcomes with confidence.

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Regression analysis explained — understanding how variables influence outcomes is essential for interpreting clinical research in this episode of This Is Why with Dr. Busti.

Dr. Busti breaks down regression analysis and how it helps identify relationships between variables while controlling for confounders. This Is Why mastering regression allows you to determine whether an intervention truly drives outcomes—or if other factors are influencing the results.

You’ll learn the difference between linear and multivariate regression, how independent and dependent variables interact, and why controlling for confounders is critical for internal validity. Dr. Busti also connects regression analysis to the bigger picture of evidence-based medicine, helping you integrate statistical tools into real clinical decision-making.

Topics Covered:
- What regression analysis actually measures
- Independent vs dependent variables
- Linear regression and line of best fit
- Multivariate (multilinear) regression explained
- Logistic regression and outcome prediction
- Identifying and controlling confounders
- Reasons variables may not show significance
- Role of sample size and statistical power

The goal = make medical education easy and clinically relevant.

Chapter Table of Contents
00:00 Introduction to Regression Analysis
01:41 Where Regression Fits in Biostatistics & Research
02:58 Why Regression Matters: Clinical Applications & Confounding
05:28 Correlation vs Regression Analysis
08:15 Simple Linear Regression Explained
10:36 Multiple Linear Regression & Adjusting for Confounders
13:18 LINE Mnemonic: Assumptions of Linear Regression
16:30 Logistic Regression and Binary Outcomes
19:35 Cox Regression and Survival Analysis
20:27 Common Regression Pitfalls: Multicollinearity, Overfitting & Sample Size
23:09 How to Interpret and Critically Appraise Regression Models

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#regressionanalysis #confounders #biostatistics #clinicalresearch #Dr Busti

Speaker:

Anthony Busti, MD, PharmD, MSc, FAHA, FNLA, is a licensed healthcare professional and medical educator with over 30 years of experience in clinical practice and academic teaching. He has trained and practiced as a nurse, pharmacist, and physician, bringing a uniquely comprehensive perspective to patient care and medical education.

Dr. Busti is dedicated to advancing evidence-based medicine and helping clinicians understand the underlying “why” behind clinical decisions to improve patient outcomes.


About This Channel:

This content is created by Anthony Busti, MD, PharmD, MSc, FAHA, FNLA, a board-certified physician with training at Johns Hopkins School of Medicine and University of Oxford and a medical educator for healthcare professionals and students. All material is based on current medical literature and evidence-based guidelines that align with principles of evidence-based medicine (EBM) and Evidence-Based Healthcare (EBHC).


Disclaimer:

This content is for educational purposes only and is not medical advice. It does not replace individualized evaluation, diagnosis, or treatment. Always seek the advice of a qualified health provider with questions about a medical condition and never delay care because of educational content.

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