Sensitivity analysis using an imputation method for missing binary data in clinical trials
Identifieur interne : 009173 ( Main/Exploration ); précédent : 009172; suivant : 009174Sensitivity analysis using an imputation method for missing binary data in clinical trials
Auteurs : Michael A. Proschan [États-Unis] ; Robert P. Mcmahon [États-Unis] ; Joanna H. Shih [États-Unis] ; Sally A. Hunsberger [États-Unis] ; Nancy L. Geller [États-Unis] ; Genell Knatterud [États-Unis] ; Janet Wittes [États-Unis]Source :
- Journal of Statistical Planning and Inference [ 0378-3758 ] ; 2001.
English descriptors
- Teeft :
- Acip, Available data, Baseline data, Binary data, Clinical trial, Clinical trials, Conditional, Conditional expectation, Conditional power, Conditional power calculations, Conservative assumption, Control patients, Control populations, Current trial, Elsevier science, Entire population, Erent, Erent models, Error rate, Event probabilities, Event probability, Event rate, Event rates, Full data, Future data, Imputation, Ischemia, Ischemia pilot, Medical therapy, Missingness, Multiple imputation, Null hypothesis, Opposite imputation, Opposite procedure, Outcome data, Particular realization, Proschan, Random sample, Respective arms, Revascularization, Revascularization arms, Same amount, Sample proportions, Sensitivity analysis, Simple methods, Standard deviation, Standard error, Statistical planning, Treatment arms, Treatment assignment, Treatment groups, Treatment strategies, Worst case analysis.
Abstract
Abstract: Missing data in clinical trials can result in biased treatment effect estimates and tests if the analysis includes only the observed data. Two simple methods of compensating for this potential bias in trials with a binary endpoint were suggested by Wittes et al. (Statist. Med. 8 (1989) 415–425). We study the statistical properties of these procedures and show that they are robust against certain model departures.
Url:
DOI: 10.1016/S0378-3758(00)00332-3
Affiliations:
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Geller</name><affiliation wicri:level="2"><country xml:lang="fr">États-Unis</country><wicri:regionArea>National Heart, Lung and Blood Institute, Office of Biostatistics Research, Rockledge Center 2, Room 8222, 6701 Rockledge Drive, MSC 7938 Bethesda, MD 20892-7938</wicri:regionArea><placeName><region type="state">Maryland</region></placeName></affiliation></author><author><name sortKey="Knatterud, Genell" sort="Knatterud, Genell" uniqKey="Knatterud G" first="Genell" last="Knatterud">Genell Knatterud</name><affiliation wicri:level="2"><country xml:lang="fr">États-Unis</country><wicri:regionArea>National Heart, Lung and Blood Institute, Office of Biostatistics Research, Rockledge Center 2, Room 8222, 6701 Rockledge Drive, MSC 7938 Bethesda, MD 20892-7938</wicri:regionArea><placeName><region type="state">Maryland</region></placeName></affiliation></author><author><name sortKey="Wittes, Janet" sort="Wittes, Janet" uniqKey="Wittes J" first="Janet" last="Wittes">Janet Wittes</name><affiliation wicri:level="2"><country xml:lang="fr">États-Unis</country><wicri:regionArea>National Heart, Lung and Blood Institute, Office of Biostatistics Research, Rockledge Center 2, Room 8222, 6701 Rockledge Drive, MSC 7938 Bethesda, MD 20892-7938</wicri:regionArea><placeName><region type="state">Maryland</region></placeName></affiliation></author></analytic><monogr></monogr><series><title level="j">Journal of Statistical Planning and Inference</title><title level="j" type="abbrev">JSPI</title><idno type="ISSN">0378-3758</idno><imprint><publisher>ELSEVIER</publisher><date type="published" when="2001">2001</date><biblScope unit="volume">96</biblScope><biblScope unit="issue">1</biblScope><biblScope unit="page" from="155">155</biblScope><biblScope unit="page" to="165">165</biblScope></imprint><idno type="ISSN">0378-3758</idno></series></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">0378-3758</idno></seriesStmt></fileDesc><profileDesc><textClass><keywords scheme="Teeft" xml:lang="en"><term>Acip</term><term>Available data</term><term>Baseline data</term><term>Binary data</term><term>Clinical trial</term><term>Clinical trials</term><term>Conditional</term><term>Conditional expectation</term><term>Conditional power</term><term>Conditional power calculations</term><term>Conservative assumption</term><term>Control patients</term><term>Control populations</term><term>Current trial</term><term>Elsevier science</term><term>Entire population</term><term>Erent</term><term>Erent models</term><term>Error rate</term><term>Event probabilities</term><term>Event probability</term><term>Event rate</term><term>Event rates</term><term>Full data</term><term>Future data</term><term>Imputation</term><term>Ischemia</term><term>Ischemia pilot</term><term>Medical therapy</term><term>Missingness</term><term>Multiple imputation</term><term>Null hypothesis</term><term>Opposite imputation</term><term>Opposite procedure</term><term>Outcome data</term><term>Particular realization</term><term>Proschan</term><term>Random sample</term><term>Respective arms</term><term>Revascularization</term><term>Revascularization arms</term><term>Same amount</term><term>Sample proportions</term><term>Sensitivity analysis</term><term>Simple methods</term><term>Standard deviation</term><term>Standard error</term><term>Statistical planning</term><term>Treatment arms</term><term>Treatment assignment</term><term>Treatment groups</term><term>Treatment strategies</term><term>Worst case analysis</term></keywords></textClass><langUsage><language ident="en">en</language></langUsage></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Abstract: Missing data in clinical trials can result in biased treatment effect estimates and tests if the analysis includes only the observed data. Two simple methods of compensating for this potential bias in trials with a binary endpoint were suggested by Wittes et al. (Statist. Med. 8 (1989) 415–425). We study the statistical properties of these procedures and show that they are robust against certain model departures.</div></front></TEI><affiliations><list><country><li>États-Unis</li></country><region><li>Maryland</li></region></list><tree><country name="États-Unis"><region name="Maryland"><name sortKey="Proschan, Michael A" sort="Proschan, Michael A" uniqKey="Proschan M" first="Michael A" last="Proschan">Michael A. Proschan</name></region><name sortKey="Geller, Nancy L" sort="Geller, Nancy L" uniqKey="Geller N" first="Nancy L" last="Geller">Nancy L. Geller</name><name sortKey="Hunsberger, Sally A" sort="Hunsberger, Sally A" uniqKey="Hunsberger S" first="Sally A" last="Hunsberger">Sally A. Hunsberger</name><name sortKey="Knatterud, Genell" sort="Knatterud, Genell" uniqKey="Knatterud G" first="Genell" last="Knatterud">Genell Knatterud</name><name sortKey="Mcmahon, Robert P" sort="Mcmahon, Robert P" uniqKey="Mcmahon R" first="Robert P" last="Mcmahon">Robert P. Mcmahon</name><name sortKey="Shih, Joanna H" sort="Shih, Joanna H" uniqKey="Shih J" first="Joanna H" last="Shih">Joanna H. Shih</name><name sortKey="Wittes, Janet" sort="Wittes, Janet" uniqKey="Wittes J" first="Janet" last="Wittes">Janet Wittes</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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