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Sample surveys: nonprobability sampling.

Sample surveys: nonprobability sampling.
Sample surveys: nonprobability sampling.
Nonprobability sampling describes any method for collecting survey data which does not utilize a full probability sampling design. Nonprobability samples are usually cheaper and easier to collect than probability samples. However, there are a number of drawbacks. Such methods can be prone to selection bias, and standard design-based methods of inference cannot be used to ensure approximately unbiased estimators of population quantities or to provide associated measures of precision. In this article, some of the more common methods of nonprobability sampling, quota sampling in particular, are introduced. Their advantages and disadvantages are discussed, and a formal framework for assessing the validity of inferences from nonprobability samples is described.
0080430767
13467-13470
Elsevier
Forster, J.J.
e3c534ad-fa69-42f5-b67b-11617bc84879
Smelser, N.J.
Baltes, P.B.
Forster, J.J.
e3c534ad-fa69-42f5-b67b-11617bc84879
Smelser, N.J.
Baltes, P.B.

Forster, J.J. (2001) Sample surveys: nonprobability sampling. In, Smelser, N.J. and Baltes, P.B. (eds.) International Encyclopedia of the Social & Behavioral Sciences. Oxford, UK. Elsevier, pp. 13467-13470. (doi:10.1016/B0-08-043076-7/00499-X).

Record type: Book Section

Abstract

Nonprobability sampling describes any method for collecting survey data which does not utilize a full probability sampling design. Nonprobability samples are usually cheaper and easier to collect than probability samples. However, there are a number of drawbacks. Such methods can be prone to selection bias, and standard design-based methods of inference cannot be used to ensure approximately unbiased estimators of population quantities or to provide associated measures of precision. In this article, some of the more common methods of nonprobability sampling, quota sampling in particular, are introduced. Their advantages and disadvantages are discussed, and a formal framework for assessing the validity of inferences from nonprobability samples is described.

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Published date: 2001
Organisations: Statistics

Identifiers

Local EPrints ID: 29963
URI: http://eprints.soton.ac.uk/id/eprint/29963
ISBN: 0080430767
PURE UUID: bd687d36-a896-474c-aeaf-484d535d4733
ORCID for J.J. Forster: ORCID iD orcid.org/0000-0002-7867-3411

Catalogue record

Date deposited: 11 May 2006
Last modified: 16 Mar 2024 02:45

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Contributors

Author: J.J. Forster ORCID iD
Editor: N.J. Smelser
Editor: P.B. Baltes

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