MISSING DATA IMPUTATION METHODS UNDER NONIGNORABLE MECHANISMS Cover Image

МЕТОДИ ЗА ВЪВЕЖДАНЕ НА ЛИПСВАЩИ СТОЙНОСТИ ПРИ НЕИГНУРИРУЕМИ МЕХАНИЗМИ
MISSING DATA IMPUTATION METHODS UNDER NONIGNORABLE MECHANISMS

Author(s): Deyan Lazarov
Subject(s): Economy
Published by: Бургаски свободен университет
Keywords: missing data; missing data mechanisms; NMAR; Selection models; Pattern mixture models

Summary/Abstract: In presented research was made an overview of the basic methods for dealing with missing data when nonignorable mechanisms exist. In the beginning different missing data mechanisms are presented. Second part shows several simple methods for Missing data imputation when mechanism is NMAR. In the next sections the basis of the Selection models and the advantages and disadvantages of this models are presented. The final section shows the essence, advantages and disadvantages of the Pattern mixture models.

  • Issue Year: XXVII/2012
  • Issue No: 1
  • Page Range: 104-114
  • Page Count: 10
  • Language: Bulgarian
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