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Titolo: Local sensitivity approximations for selectivity bias
Autore: Copas, J; Eguchi, S;
- Indirizzi:
- Univ Warwick, Dept Stat, Coventry CV4 7AL, W Midlands, England Univ Warwick Coventry W Midlands England CV4 7AL 7AL, W Midlands, England Inst Stat Math, Tokyo, Japan Inst Stat Math Tokyo JapanInst Stat Math, Tokyo, Japan
- Titolo Testata:
- JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY
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volume: 63,
anno: 2001,
parte:, 4
pagine: 871 - 895
- SICI:
- 1369-7412(2001)63:<871:LSAFSB>2.0.ZU;2-T
- Fonte:
- ISI
- Lingua:
- ENG
- Soggetto:
- NON-IGNORABLE NONRESPONSE; NONIGNORABLE NONRESPONSE; PERMUTATION INFERENCES; SAMPLE SELECTION; MODELS; VARIABLES; SUBJECT;
- Keywords:
- ignorability; missing data; selection bias; sensitivity analysis;
- Tipo documento:
- Article
- Natura:
- Periodico
- Settore Disciplinare:
- Physical, Chemical & Earth Sciences
- Citazioni:
- 32
- Recensione:
- Indirizzi per estratti:
- Indirizzo: Copas, J Univ Warwick, Dept Stat, Coventry CV4 7AL, W Midlands, England Univ Warwick Coventry W Midlands England CV4 7AL dlands, England
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- Citazione:
- J. Copas e S. Eguchi, "Local sensitivity approximations for selectivity bias", J ROY STA B, 63, 2001, pp. 871-895
Abstract
Observational data analysis is often based on tacit assumptions of ignorability or randomness. The paper develops a general approach to local sensitivity analysis for selectivity bias, which aims to study the sensitivity of inference to small departures from such assumptions. If M is a model assuming ignorability, we surround M by a small neighbourhood Ar defined in the sense of Kullback-Leibler divergence and then compare the inference for models in Ar with that for M. Interpretable bounds for such differences are developed. Applications to missing data and to observational comparisons are discussed. Local approximations to sensitivity analysis are model robust andcan be applied to a wide range of statistical problems.
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Documento generato il 26/05/13 alle ore 07:32:40