Missing Data – ONLINE

Course details

statistics course | level: intermediate | register now
for questions related to this event, contact ugent@flames-statistics.com
affiliation: Ghent University

Abstract

Day 1:
1. Introduction
- What is missing data;
- Consequences and effects of missing data;
- Missing data and inference;
- Illustration of consequences and effects with some examples.
2. Fundamental Concepts
- Missing data patterns;
- Missing data mechanisms;
- Types of missing data mechanisms;
- Illustration with some examples.
3. Introduction to missing data methodology
- Ad-Hoc Methods and why not to use them;
- Imputation-based procedures.

Day 2:
1. Missing Data Methodology (cont’d)
- Visualize missing Data;
- Weighting procedures;
- Model-based procedures -likelihood methods;
- Sensitivity analysis.
2. Case Studies
- Missing data in a longitudinal study;
- Missing data in a survival analysis.


Day 3:
- Hands-on session.

Prerequisites

To take this course, you should have a good working knowledge of the principles and practice of multiple linear regression, as well as elementary statistical inference.

We will use R/Rstudio packages to demonstrate implementation of certain methods; thus, some familiarity with R is desirable !!! Bring your own laptop, with R installed on it !!!

R can be downloaded for free from http://www.r-project.org/

Background readings

Flexible Imputation of Missing Data. Free online book. Stef van Buuren, https://stefvanbuuren.name/fimd/

Fee

PhDs and postdocs of a Flemish university: 0 €
Other academics: 120 €
Non-profit/Social sector: 200 €
Private sector: 400 €

Venue

Online course

Instructor

Emmanuel Abatih