Short Course Material


 

Introduction to Data Integration for combining probability and nonprobability samples

Nonprobability samples have been used frequently in practice including education, medical study, and public opinion research. Due to selection bias, naïve estimates without adjustments by using nonprobability samples may lead to misleading results. In this course, we will discuss some commonly used data integration methods for reducing the selection bias of nonprobability samples.

9/29/2023 Noon - 2:00 pm (CDT)

Hudson College of Public Health Auditorium (CHB 220)

Lunch Provided for first 25 in-person participants

Registration Link

Flyer

Workshop materials (slides) (code and data) (new R code)


 

 

Previous Topics

 

Introduction to Complex Survey Data Analysis

Biases in Diagnostic and Prognostic Research

 

Propensity Score Analysis in Epidemiologic Research: An Introduction

Part 1

Part 2

 

 

Prediction Models & Risk Score Development in Clinical Research

 

 

Multplicity Adjustment in Design & Analysis of Clinical Trails Agenda 9/42/2021