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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/12928

Title: Sensitivity analysis for incomplete continuous data
Authors: Poleto, Frederico Z.
Molenberghs, Geert
Paulino, Carlos Daniel
Singer, Julio M.
Issue Date: 2011
Publisher: SPRINGER
Citation: TEST, 20(3), p. 589-606
Abstract: Models for missing data are necessarily based on untestable assumptions whose effect on the conclusions are usually assessed via sensitivity analysis. To avoid the usual normality assumption and/or hard-to-interpret sensitivity parameters proposed by many authors for such purposes, we consider a simple approach for estimating means, standard deviations and correlations. We do not make distributional assumptions and adopt a pattern-mixture model parameterization which has easily interpreted sensitivity parameters. We use the so-called estimated ignorance and uncertainty intervals to summarize the results and illustrate the proposal with a practical example. We present results for both the univariate and the multivariate cases.
Notes: [Poleto, Frederico Z.; Singer, Julio M.] Univ Sao Paulo, Inst Matemat & Estatist, BR-05314970 Sao Paulo, Brazil. [Molenberghs, Geert] Univ Hasselt, I BioStat, B-3590 Diepenbeek, Belgium. [Molenberghs, Geert] Katholieke Univ Leuven, B-3000 Louvain, Belgium. [Paulino, Carlos Daniel] Univ Tecn Lisbon, Inst Super Tecn, P-1049001 Lisbon, Portugal. [Paulino, Carlos Daniel] CEAUL FCUL, P-1049001 Lisbon, Portugal. fpoleto@ime.usp.br; geert.molenberghs@uhasselt.be; dpaulino@math.ist.utl.pt; jmsinger@ime.usp.br
URI: http://hdl.handle.net/1942/12928
Link to publication: https://www.researchgate.net/publication/225566053_Sensitivity_analysis_for_incomplete_continuous_data
DOI: 10.1007/s11749-010-0219-x
ISI #: 000297125000012
ISSN: 1133-0686
Category: A1
Type: Journal Contribution
Validation: ecoom, 2012
Appears in Collections: Research publications

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