Multiple Regression Analysis in Public Health

Multiple Regression Analysis in Public Health

This course is part of Biostatistics in Public Health Specialization

Instructor: John McGready, PhD, MS

Sponsored by Louisiana Workforce Commission

15,812 already enrolled

4 modules

Gain insight into a topic and learn the fundamentals.

4.7

(298 reviews)

Beginner level

Recommended experience

14 hours to complete

3 weeks at 4 hours a week

Flexible schedule

Learn at your own pace

4 modules

Gain insight into a topic and learn the fundamentals.

4.7

(298 reviews)

Beginner level

Recommended experience

14 hours to complete

3 weeks at 4 hours a week

Flexible schedule

Learn at your own pace

What you'll learn

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

Skills you'll gain

Details to know

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Assessments

7 assignments

Taught in English

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This course is part of the Biostatistics in Public Health Specialization

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There are 4 modules in this course

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.

Within this module, an overview of multiple regression will be provided. Additionally, examples and applications will be examined. A practice quiz is provided to test your knowledge before completing the graded quiz.

What's included

9 videos2 readings2 assignments

9 videosTotal 177 minutes

Multiple Regression: An Overview13 minutesPreview module
Multiple Linear Regression: Some Examples23 minutes
Multiple Linear Regression: Basics of Model Estimation, and Handling Uncertainty in the Resulting Estimates14 minutes
Estimate Group Means and Mean Differences for Groups Who Differ in More than One Predictor with Multiple Linear Regression9 minutes
The “Linearity” Assumption and Estimating Amount of Variability Explained by Multiple Predictors21 minutes
Examples from the Literature21 minutes
Investigating Effect Modification with Multiple Linear Regression (Forthcoming)20 minutes
Investigating Effect Modification with Multiple Linear Regression—More Examples, For Those Interested18 minutes
Additional Examples of Multiple Linear Regression34 minutes

2 readingsTotal 25 minutes

Solutions to Practice Quiz on Multiple Linear Regression15 minutes
Solutions to Summative Quiz 110 minutes

2 assignmentsTotal 60 minutes

An Overview of Multiple Regression for Estimation, Adjustment, and Basic Prediction, and Multiple Linear Regression30 minutes
Practice Quiz: An Overview of Multiple Regression for Estimation, Adjustment, and Basic Prediction, and Multiple Linear Regression30 minutes

Module two covers examples of multiple logistic regression, basics of model estimates, and a discussion of effect modification. In addition to lectures, you will also be completing a practice quiz and graded quiz.

What's included

8 videos2 readings2 assignments

8 videosTotal 173 minutes

Multiple Logistic Regression: Some Examples24 minutesPreview module
Multiple Logistic Regression: Basics of Model Estimation, and Handling Uncertainty in the Resulting Estimates18 minutes
Estimating Group Odds and Proportions, and Odds Ratios for Groups Who Differ in More than One Predictor with Multiple Linear Regression24 minutes
The “Linearity” Assumption and A Brief Note about Prediction with Multiple Logistic Regression27 minutes
Examples from the Literature26 minutes
Investigating Effect Modification with Multiple Logistic Regression, Part 118 minutes
Investigating Effect Modification with Multiple Logistic Regression, Part 210 minutes
Additional Examples21 minutes

2 readingsTotal 30 minutes

Solutions to Practice Quiz Items 1-920 minutes
Solutions to Quiz on Logistic Regression10 minutes

2 assignmentsTotal 60 minutes

Multiple Logistic Regression30 minutes
Practice Quiz: Multiple Logistic Regression30 minutes

The last module for this class focuses on multiple Cox regression, the “Linearity” assumption, examples, and applications. You will complete a practice quiz, graded quiz, and project.

What's included

5 videos2 readings2 assignments

5 videosTotal 95 minutes

Some Examples17 minutesPreview module
Basics of Model Estimation and Handling Uncertainty in the Resulting Estimates18 minutes
Estimating Hazard Ratios for Groups who Differ in more than one Predictor with Multiple Cox Regression12 minutes
The "Linearity" Assumption and Prediction with Multiple Cox Regression21 minutes
Examples from the Literature25 minutes

2 readingsTotal 30 minutes

Solutions To Multiple Cox Regression Practice Quiz20 minutes
Solutions: Summative Quiz (Multiple Cox Regression)10 minutes

2 assignmentsTotal 60 minutes

Multiple Cox Regression, and Course Concepts30 minutes
Practice Quiz: Multiple Cox Regression30 minutes

During this module, you get the chance to demonstrate what you've learned by putting yourself in the shoes of biostatistical consultant on two different studies, one about self-administration of injectable contraception and one about medical appointment scheduling in Brazil. The two research teams have asked you to help them interpret previously published results in order to inform the planning of their own studies. If you've already taken other courses in this specialization, then this scenario will be familiar.