Title of article :
On Hierarchical Multiple Imputation Method for Handling Missing Data
Author/Authors :
Sheikhy ، Ayyub Department of Statistics - Faculty of Mathematics and Computer - Shahid Bahonar University of Kerman , Arabpour ، Alireza Department of Statistics - Faculty of Mathematics and Computer - Shahid Bahonar University of Kerman , Mashinchi ، Mashallah Department of Statistics - Faculty of Mathematics and Computer - Shahid Bahonar University of Kerman , Pourmousa ، R. Department of Statistics - Faculty of Mathematics and Computer - Shahid Bahonar University of Kerman , Rezapour ، Mohsen Department of Statistics - Faculty of Mathematics and Computer - Shahid Bahonar University of Kerman , Roastami ، Mohammad Javad Department of Computer Engineering - Kerman Chamber of Commerce, Industries, Mines and Agriculture - Shahid Bahonar University of Kerman , Mohsen ، Khosravi Department of Statistics - Faculty of Mathematics and Computer - Shahid Bahonar University of Kerman , Abbdollah Nejad ، Amin Kerman Chamber of Commerce , Badakhshan ، Abed Department of Statistics - Faculty of Mathematics and Computer - Shahid Bahonar University of Kerman
Abstract :
In this work we carry out a multiple imputation technique for handling missing observations. We propose an algorithm, which performs a hierarchical multiple imputation using edition rules to impute missing values. We assess our algorithm using a simulation study and a numerical application of our algorithm in dataset of Kerman Chamber of Commerce, Industries, Mines and Agriculture is presented for more illustration.
Keywords :
Missing Data , Multiple Imputation , Editing Rules , Data Cleaning
Journal title :
Journal of Mahani Mathematical Research Center
Journal title :
Journal of Mahani Mathematical Research Center
