Skip to main content

Applied Health InformaticsData Science for Health Informatists

Welcome
Chapter 1 - Data Acquisition and Notebooks
Chapter 2 - Data Processing and Cleaning
Chapter 3 - Exploratory Data Analysis (EDA)
Chapter 4 - Visualizations and Dashboards
Chapter 5 - Inferential Statistics
Chapter 6 - Regression Analyses
Chapter 7 - Geospatial Data
Chapter 8 - ML based Classification Techniques
Chapter 9 - Ensemble Methods in Predictive Analytics
Chapter 10 - Unsupervised Learning and Model Interpretability
Chapter 11 - Time Series Analysis
Chapter 12 - Natural Language Processing (NLP)
Chapter 13 - Advanced Data Acquisition: APIs and Web-scraping
Chapter 14 - Automating Data Tasks: Cron Jobs and Workflow Automation
Chapter 15 - Deployment Options: Flask, FastAPI, Django, and Streamlit

Chapter 6 - Regression Analyses
Resources

Resources

StatsModels for Clinical Research

6.5 Logistic Regression for Disease Prediction

Copyright © 2024 Hants Williams, PhD, RN