 Non-Response and Its TreatmentsSarjinder Singh
Chapter 12 in Advanced Sampling Theory with Applications, 2003, pp 975-1064 from Springer Abstract: Abstract Incompleteness or non-response in the form of absence, censoring, or grouping is a troubling issue of many data sets. Statisticians have recognized for some time that failure to account for the stochastic nature of incompleteness or non-response can spoil the nature of data. There are several factors which effect the non-response rate in any particular inquiry. Some of these factors are the type of information being collected, the official status of the surveying agency, the extent of publicity, the legal obligations of the respondents, the time of visit by the enumerator and length of the schedule, etc.. Hansen and Hurwitz (1946) were the first to deal with the problem of incomplete samples in mail surveys. It is a well known fact that mail surveys or telephone surveys are most commonly used by most of the bureaucratic or business organisations because of their low cost. Rubin (1976) has defined three key concepts: Missing at random (MAR), Observed at random (OAR), and parameter distinctness (PD). Keywords: Auxiliary Variable; Unbiased Estimator; Response Probability; Finite Population; Inclusion Probability (search for similar items in EconPapers) There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it. Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-94-007-0789-4_12 Ordering information: This item can be ordered from DOI: 10.1007/978-94-007-0789-4_12 Access Statistics for this chapter More chapters in Springer Books from Springer |
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