Missing Data: Consequences and Solutions (WV81)

Course Content
Although researchers do their best to avoid missing data, it is a common problem in medical and epidemiological studies. How large your missing data problem is and how to deal with it depends on how much data is missing and why your data are missing. This two-day course provides you with tools how to evaluate and handle missing data in medical and epidemiological studies with different missing data rates.

Learning objectives, training objectives
The participant is able to distinguish between different missing data mechanisms called missing completely at random (MCAR), missing at random (MAR) and missing not at random (MNAR).

Target Audience
The course is designed for everybody who wants to learn about missing data because missing data may be present in your own research you want to learn how to judge other articles or research grants.

Qualifications
The following concepts are assumed known by participants at the start of this course: - Knowledge of basic statistical tests as t-tests and regression analyses. - Knowledge of some basic SPSS commands.

Notes
We use an interactive Learn Management System for this online course. Here you can find all course materials at least one week before the start of the course

Register via the website. The course will be an online course because of Covid-19

Ms. Drs Yvonne van Loon