Dealing with missing data in regression models

when 29 June 2017 - 30 June 2017
language English
duration 1 week
credits 10 EC

Most researchers in the social and behavioural sciences have encountered the problem of missing data: It seriously complicates the statistical analysis of data, and simply ignoring it is not a good strategy. A general and statistically valid technique to analyse incomplete data is multiple imputation, which is rapidly becoming the standard in social and behavioural science research.

Target group

Students, researchers, business professionals who need to develop good quality surveys and/or need to apply appropriate and up-to-date statistical methods. At the conclusion of the Summer School, participants will receive a certificate for each course and with the number of hours attended.

Course aim

The aim of this course is to enhance participants’ knowledge in imputation methodology, and to provide a flexible solution to their incomplete data problems. The course will outline a step-by-step approach toward creating high quality imputations, and provide guidelines how the results can be reported

Fee info

EUR 0: Several Fees; check the website