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Multiple Regression Analysis in Public Health
  • Level Foundation
  • Duration 14 hours
  • Course by Johns Hopkins University
  • Offered by

About

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.

Modules

Multiple Regression

    • 9 Videos
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9 Videos

  • 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

Formative Assessment

    • 1 Readings
    • 1 Assignment
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1 Assignment

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

1 Readings

  • Solutions to Practice Quiz on Multiple Linear Regression

Summative Assessment

    • 1 Readings
    • 1 Assignment
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1 Assignment

  • An Overview of Multiple Regression for Estimation, Adjustment, and Basic Prediction, and Multiple Linear Regression

1 Readings

  • Solutions to Summative Quiz 1

Multiple Logistic Regression

    • 8 Videos
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8 Videos

  • 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

Formative Assessment

    • 1 Readings
    • 1 Assignment
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1 Assignment

  • Practice Quiz: Multiple Logistic Regression

1 Readings

  • Solutions to Practice Quiz Items 1-9

Summative Assessment

    • 1 Readings
    • 1 Assignment
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1 Assignment

  • Multiple Logistic Regression

1 Readings

  • Solutions to Quiz on Logistic Regression

Multiple Cox Regression

    • 5 Videos
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5 Videos

  • 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

Formative Assessment

    • 1 Readings
    • 1 Assignment
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1 Assignment

  • Practice Quiz: Multiple Cox Regression

1 Readings

  • Solutions To Multiple Cox Regression Practice Quiz

Summative Assessment

    • 1 Readings
    • 1 Assignment
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1 Assignment

  • Multiple Cox Regression, and Course Concepts

1 Readings

  • Solutions: Summative Quiz (Multiple Cox Regression)

Reading: Biostatistical Consulting Project

    • 1 Readings
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1 Readings

  • Biostatistical Consulting Project

Quiz: Course Project Quiz (1 attempt per day allowed)

    • 1 Assignment
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1 Assignment

  • Project

Auto Summary

Unlock the power of biostatistics in public health with this foundational Coursera course. Dive into multiple regression analysis, learning to predict outcomes using various methods. Topics include logistic regression, Spline approach, confidence intervals, p-values, and more. Ideal for beginners, this 840-minute course offers practical data interpretation and calculations using real study data. Available under Starter and Professional subscriptions, it's perfect for those looking to enhance their statistical skills in health and fitness.

John McGready, PhD, MS
Instructor

John McGready, PhD, MS