Perfect the Imperfect Data – How to Deal with Missing Data in Practice

No data is perfect, because of imperfect study design or the data collection process. Missing data is often inevitable. In order to help researchers handle missing data properly, cause, consequence, analysis methods and prevention suggestions of missing data will be introduced. In this workshop. Case studies in SPSS will be presented.


  1. Types of Missing Data
  2. Consequence of Missing Data
  3. Analysis of Missing Data
  4. Preventing Missing Data