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Multiple Regression Analysis in Public Health

Approx. 14 hours to complete

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Course Summary

Learn how to use multiple regression analysis in public health research to identify patterns and relationships between variables and make informed decisions.

Key Learning Points

Understand the principles and techniques of multiple regression analysis
Learn how to use regression analysis to identify risk factors and evaluate interventions
Develop skills in data analysis and interpretation for public health research

Learning Outcomes

Understand the principles and techniques of multiple regression analysis
Develop skills in data analysis and interpretation for public health research
Apply regression analysis to identify risk factors and evaluate interventions

Prerequisites or good to have knowledge before taking this course

Basic knowledge of statistics
Familiarity with public health research

Course Difficulty Level

Intermediate

Course Format

Online
Self-paced

Similar Courses

Applied Regression Analysis
Data Analysis in Public Health

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Description

Biostatistics is the application of statistical reasoning to the life sciences, and it's the key to unlocking the data gathered by researchers and the evidence presented in the scientific public health literature. In this course, you'll extend simple regression to the prediction of a single outcome of interest on the basis of multiple variables. Along the way, you'll be introduced to a variety of methods, and you'll practice interpreting data and performing calculations on real data from published studies. Topics include multiple logistic regression, the Spline approach, confidence intervals, p-values, multiple Cox regression, adjustment, and effect modification.

Knowledge

Practice multiple regression methods to determine relationships between an outcome and multiple predictors
Use the Spline approach for non-linear relationships with continuous predictors
Perform calculations with multiple predictor variables

Outline

An Overview of Multiple Regression for Estimation, Adjustment, and Basic Prediction, and Multiple Linear Regression
Multiple Regression: An Overview
Multiple Linear Regression: Some Examples
Multiple Linear Regression: Basics of Model Estimation, and Handling Uncertainty in the Resulting Estimates
Estimate Group Means and Mean Differences for Groups Who Differ in More than One Predictor with Multiple Linear Regression
The “Linearity” Assumption and Estimating Amount of Variability Explained by Multiple Predictors
Examples from the Literature
Investigating Effect Modification with Multiple Linear Regression (Forthcoming)
Investigating Effect Modification with Multiple Linear Regression—More Examples, For Those Interested
Additional Examples of Multiple Linear Regression
Solutions to Practice Quiz on Multiple Linear Regression
Solutions to Summative Quiz 1
Practice Quiz: An Overview of Multiple Regression for Estimation, Adjustment, and Basic Prediction, and Multiple Linear Regression
An Overview of Multiple Regression for Estimation, Adjustment, and Basic Prediction, and Multiple Linear Regression

Multiple Logistic Regression
Multiple Logistic Regression: Some Examples
Multiple Logistic Regression: Basics of Model Estimation, and Handling Uncertainty in the Resulting Estimates
Estimating Group Odds and Proportions, and Odds Ratios for Groups Who Differ in More than One Predictor with Multiple Linear Regression
The “Linearity” Assumption and A Brief Note about Prediction with Multiple Logistic Regression
Examples from the Literature
Investigating Effect Modification with Multiple Logistic Regression, Part 1
Investigating Effect Modification with Multiple Logistic Regression, Part 2
Additional Examples
Solutions to Practice Quiz Items 1-9
Solutions to Quiz on Logistic Regression
Practice Quiz: Multiple Logistic Regression
Multiple Logistic Regression

Multiple Cox Regression
Some Examples
Basics of Model Estimation and Handling Uncertainty in the Resulting Estimates
Estimating Hazard Ratios for Groups who Differ in more than one Predictor with Multiple Cox Regression
The "Linearity" Assumption and Prediction with Multiple Cox Regression
Examples from the Literature
Soluitons To Multiple Cox Regression Practice Quiz
Solutions: Summative Quiz (Multiple Cox Regression)
Practice Quiz: Multiple Cox Regression
Multiple Cox Regression, and Course Concepts

Course Project
Biostatistical Consulting Project
Project

Summary of User Reviews

Read reviews of Multiple Regression Analysis in Public Health from the world's top universities and institutions. Overall rating of the course is great. Many users appreciated the in-depth coverage of the topic.

Pros from User Reviews

In-depth coverage of the topic
Well-structured content
Good balance between theory and application
Great resources and materials
Engaging and knowledgeable instructors

Cons from User Reviews

Some users found the course too technical
Few users had trouble with the quizzes
Some users felt the course lacked practical examples
Few users didn't like the pace of the course
Some users thought that the course was too lengthy

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