Multiple Imputation Method for Missing Data
Hawkar Qasim Biredawood
hawkar.Birdawod@cihanuniversity.edu.iq
Abstract- Missing or incomplete data is a very serious problem in many fields of research, such as in active media technology, opinion polls, market research surveys, mail enquiries, medical studies, and other scientific experiments. Missing data frequently complicates scientific investigations. The development of statistical methods to address missing data has been an active area of research in recent decades. Determining the appropriate analytic approach in the presence of incomplete observations is a major question for data analysts. Multiple imputation (MI) appears to be one of the most attractive methods for general purpose handling of missing data in uni variate and multivariate analysis.
Keywords- Imputation Method, Missing Data, multivariate analysis
Date: 11/01/2018
Place: Business Administration Department, Hall (8201)