Multiple Regression Analysis in Public Health

Coursera Multiple Regression Analysis in Public Health

Platform
Coursera
Provider
Johns Hopkins University
Effort
3-4 hours a week
Length
4 weeks
Language
English
Credentials
Paid Certificate Available
Part of
Course Link
Overview
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.

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

Syllabus
  1. An Overview of Multiple Regression for Estimation, Adjustment, and Basic Prediction, and Multiple Linear Regression
  2. Multiple Logistic Regression
  3. Multiple Cox Regression
  4. Course Project

Taught by

John McGready, PhD, MS
Author
Coursera
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