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.
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Biostatistics in Public Health SpecializationJohns Hopkins UniversityAbout this Course
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Beginner Level
The recommended math prerequisite is up through and including basic algebra including logarithms and the equation of a line.
Approx. 14 hours to complete
English
Subtitles: Arabic, French, Portuguese (European), Chinese (Simplified), Italian, Vietnamese, Korean, German, Russian, Turkish, English, Spanish
What you will 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 will gain
effect modifcationProportional Hazards ModelRegression AnalysisSpline approach
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Course 4 of 4 in the
Flexible deadlines
Reset deadlines in accordance to your schedule.
Beginner Level
The recommended math prerequisite is up through and including basic algebra including logarithms and the equation of a line.
Approx. 14 hours to complete
English
Subtitles: Arabic, French, Portuguese (European), Chinese (Simplified), Italian, Vietnamese, Korean, German, Russian, Turkish, English, Spanish
Offered by
Johns Hopkins University
The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.
Syllabus - What you will learn from this course
4 hours to complete
An Overview of Multiple Regression for Estimation, Adjustment, and Basic Prediction, and Multiple Linear Regression
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.
4 hours to complete
9 videos (Total 177 min), 2 readings, 2 quizzes
9 videos
Multiple Linear Regression: Some Examples23m
Multiple Linear Regression: Basics of Model Estimation, and Handling Uncertainty in the Resulting Estimates14m
Estimate Group Means and Mean Differences for Groups Who Differ in More than One Predictor with Multiple Linear Regression9m
The “Linearity” Assumption and Estimating Amount of Variability Explained by Multiple Predictors21m
Examples from the Literature21m
Investigating Effect Modification with Multiple Linear Regression (Forthcoming)20m
Investigating Effect Modification with Multiple Linear Regression—More Examples, For Those Interested18m
Additional Examples of Multiple Linear Regression34m
2 readings
Solutions to Practice Quiz on Multiple Linear Regression10m
Solutions to Summative Quiz 110m
2 practice exercises
Practice Quiz: An Overview of Multiple Regression for Estimation, Adjustment, and Basic Prediction, and Multiple Linear Regression30m
An Overview of Multiple Regression for Estimation, Adjustment, and Basic Prediction, and Multiple Linear Regression30m
4 hours to complete
Multiple Logistic Regression
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.
4 hours to complete
8 videos (Total 173 min), 2 readings, 2 quizzes
8 videos
Multiple Logistic Regression: Basics of Model Estimation, and Handling Uncertainty in the Resulting Estimates18m
Estimating Group Odds and Proportions, and Odds Ratios for Groups Who Differ in More than One Predictor with Multiple Linear Regression24m
The “Linearity” Assumption and A Brief Note about Prediction with Multiple Logistic Regression27m
Examples from the Literature26m
Investigating Effect Modification with Multiple Logistic Regression, Part 118m
Investigating Effect Modification with Multiple Logistic Regression, Part 210m
Additional Examples21m
2 readings
Solutions to Practice Quiz Items 1-910m
Solutions to Quiz on Logistic Regression10m
2 practice exercises
Practice Quiz: Multiple Logistic Regression30m
Multiple Logistic Regression30m
3 hours to complete
Multiple Cox Regression
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.
3 hours to complete
5 videos (Total 95 min), 2 readings, 2 quizzes
5 videos
Basics of Model Estimation and Handling Uncertainty in the Resulting Estimates18m
Estimating Hazard Ratios for Groups who Differ in more than one Predictor with Multiple Cox Regression12m
The "Linearity" Assumption and Prediction with Multiple Cox Regression21m
Examples from the Literature25m
2 readings
Soluitons To Multiple Cox Regression Practice Quiz10m
Solutions: Summative Quiz (Multiple Cox Regression)10m
2 practice exercises
Practice Quiz: Multiple Cox Regression30m
Multiple Cox Regression, and Course Concepts30m
2 hours to complete
Course Project
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.
2 hours to complete
1 reading
1 reading
Biostatistical Consulting Project10m
1 practice exercise
Project2h
Reviews
TOP REVIEWS FROM MULTIPLE REGRESSION ANALYSIS IN PUBLIC HEALTH
by DKJul 25, 2020
lecture pattern gives enthusiasm in learning and solving quiz sessions. explanations for the solutions gives immense strength and confidence in learning. Excellant course and marvellous experience
by BVApr 23, 2020
This course covers all types of Multiple Regressions. Instructor explained the complex topics in simple language. Relevant examples from clinical field and thorough explanation by the Instructor.
by UKJul 29, 2019
The course is well structured. The numerous examples and practice questions help the student apply the concepts learned. I love the fact that almost every question was from a real article.
by AAJun 20, 2020
Excellent Course. The video lectures are thorough and provide many examples to help explain the concepts. If this professor produces more courses, I will certainly take them.
About the Biostatistics in Public Health Specialization
This specialization is intended for public health and healthcare professionals, researchers, data analysts, social workers, and others who need a comprehensive concepts-centric biostatistics primer. Those who complete the specialization will be able to read and respond to the scientific literature, including the Methods and Results sections, in public health, medicine, biological science, and related fields. Successful learners will also be prepared to participate as part of a research team.
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