Handling Missing Data in Ranked Set Sampling

The existence of missing observations is a very important aspect to be considered in the application of survey sampling, for example. In human populations they may be caused by a refusal of some interviewees to give the true value for the variable of interest. Traditionally, simple random sampling i...

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Bibliographic Details
Main Author: Bouza-Herrera, Carlos N. (Author)
Corporate Author: SpringerLink (Online service)
Format: Electronic eBook
Language:English
Published: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013.
Series:SpringerBriefs in Statistics,
Subjects:
Online Access:Full Text via HEAL-Link
Table of Contents:
  • Preface
  • Missing Observations and Data Quality Improvement
  • Sampling Using Ranked Sets: Basic Concepts
  • The Non Response  Problem: Sub-sampling among the Non Respondents
  • Imputation of the Missing Data
  • Some Numerical Studies of the Behavior of RSS.