Handling Missing Data in Ranked Set Sampling

• Main Author: Bouza-Herrera, Carlos N. (Author)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic
• Language: English
• Published: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013.
• Series: SpringerBriefs in Statistics,
• Subjects: Statistics.; Mathematical statistics.; Statistical Theory and Methods.; Statistics for Life Sciences, Medicine, Health Sciences.; Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law.; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
• Online Access: https://ezaccess.library.uitm.edu.my/login?url=http://dx.doi.org/10.1007/978-3-642-39899-5

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...

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.