Skip to main content
  • Main Menu
  • Utility Menu
  • Search
University Logo
HARVARD.EDU

  • Home
  • Syllabus
  • Announcements
  • Lecture Notes
  • Lecture Videos
  • Resources
  • Our Community
HOME / DOCUMENTS / LECTURE NOTES FOR ADVANCED QUANTITATIVE POLITICAL METHODOLOGY /

Models for Missing Data

  • Lecture Notes for Advanced Quantitative Political Methodology
    • Introduction
    • Theories of Inference
    • Models for Binary Outcome Variables
    • Assorted Models for Single Variable Outcomes
    • Model Evaluation
    • Research Designs for Causal Inference
    • Detecting and Reducing Model Dependence in Causal Inference
    • Multiple Equation Models
    • Models for Missing Data
    • Anchoring Vignettes for Interpersonally Incomparable Survey Responses
    • Supplement: What's the Big Idea?

The lecture slides are here and a handout for one-page-at-a-time (color) printing is here. 

Lecture 9

"Models for Missing Data" covers the following topics:

  1. Overview
  2. Missingness Assumptions
  3. Application Specific Methods
  4. Multiple Imputation
  5. Computational Algorithms
  6. What Can Go Wrong
  7. Time Series, Cross-Sectional Imputations
  • Printer-friendly version

Share Gov2001

Admin Login
OpenScholar
Copyright © 2019 The President and Fellows of Harvard College | Accessibility | Report Copyright Infringement