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.
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
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4.7
(296 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
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
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 4 modules in this course
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
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
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
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.
What's included
1 reading1 assignment
Instructor
Instructor ratings
4.8 (75 ratings)Offered by
Recommended if you're interested in Health Informatics
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4.7
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Showing 3 of 296
FN
5
Reviewed on Aug 1, 2019
Incredible way of teaching biostatistics using by just adding more complexity to the same exercises in a gradual form!
CN
5
Reviewed on Aug 30, 2019
The course was five stars, there were some quiz issues and a few numerical issues, but I learned a lot and appreciate the time and effort put into the content. Thank you!
AB
5
Reviewed on Apr 21, 2020
A wonderful look at multiple regression, including effect modification, interactions, and adjusted slopes.
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