13 Mar Missing Data (fully booked)
13/03/2019 - 15/03/2019
10:00 am - 4:00 pm
statistics course | level: advanced
registrations and venue via University of Antwerp
The course will provide an introduction to the issues raised by missing data and it will illustrate the shortcomings of ad-hoc methods like deletion, recoding, complete case analysis for 'handling' missing data. Methods like multiple imputation, inverse probability weighting and likelihood procedures for statistical analysis with missing data will be discussed and contrasted. Other topics include some accessible methods for exploring the sensitivity of inference to the missing at random assumption. Special emphasis is given to the problem of missing data into specific contexts (longitudinal studies, time-to-event studies).
- 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.
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.
- Hands-on session.
Virtually anyone who does statistical analysis can benefit from this course.
Venue and timing:
Wednesday 13th + Thursday 14th March, 2019 from 10:00 - 16:00
Friday 15th March, 2019 from 10:00 - 13:00
University of Antwerp, City Campus
Prinsstraat 13, 2000 Antwerp
13/03: 10u-16u K.201
14/03: 10u-13u M103, 13-16u E.207
15/03: 10u-13u K.203
For a map of the venue see www.uantwerpen.be/en/campus-life/on-your-way-to-campus/stadscampus-campus-mutsaard/
PhDs and postdocs of a Flemish University: free
Other academics: €150
Non-profit/social sector: €250
Private sector: €500
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/
Dr Emmanuel Abatih