A unified approach for analyzing exchangeable binary data with applications to developmental toxicity studies
In this article, we present a general procedure to analyze exchangeable binary data that may also be viewed as realizations of binomial mixtures. Our approach unifies existing models and is practical and computationally easy. Resulting from completely monotonic functions, we introduce a rich family...
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| Veröffentlicht in: | Statistics in medicine 2009-09, Vol.28 (20), p.2580-2604 |
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| creator | Dang, Xin Keeton, Stephine Lena Peng, Hanxiang |
| description | In this article, we present a general procedure to analyze exchangeable binary data that may also be viewed as realizations of binomial mixtures. Our approach unifies existing models and is practical and computationally easy. Resulting from completely monotonic functions, we introduce a rich family of parametric parsimonious binomial mixtures, including the incomplete Beta‐, Gamma‐, Normal‐, and Poisson‐binomial, generalizing the Beta‐binomial. We show that the family is closed under convex linear combinations, products, and composites. We also give the moments and the Markov property of the family. With such distributions, we can perform statistical inference on correlated binary data and, in particular, overdispersed data. We propose a regression procedure that generalizes logistic regression. We provide a forward model selection procedure. We run a small simulation to validate the inclusion of the binomial distribution. Finally, we apply the proposed procedure to analyze the 2, 4, 5‐Trichlorophenoxyacetic acid and E2 data and compare the results with existing procedures. Copyright © 2009 John Wiley & Sons, Ltd. |
| doi_str_mv | 10.1002/sim.3638 |
| format | Article |
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Med</addtitle><description>In this article, we present a general procedure to analyze exchangeable binary data that may also be viewed as realizations of binomial mixtures. Our approach unifies existing models and is practical and computationally easy. Resulting from completely monotonic functions, we introduce a rich family of parametric parsimonious binomial mixtures, including the incomplete Beta‐, Gamma‐, Normal‐, and Poisson‐binomial, generalizing the Beta‐binomial. We show that the family is closed under convex linear combinations, products, and composites. We also give the moments and the Markov property of the family. With such distributions, we can perform statistical inference on correlated binary data and, in particular, overdispersed data. We propose a regression procedure that generalizes logistic regression. We provide a forward model selection procedure. We run a small simulation to validate the inclusion of the binomial distribution. Finally, we apply the proposed procedure to analyze the 2, 4, 5‐Trichlorophenoxyacetic acid and E2 data and compare the results with existing procedures. Copyright © 2009 John Wiley & Sons, Ltd.</description><subject>2,4,5-Trichlorophenoxyacetic Acid - adverse effects</subject><subject>Abnormalities, Drug-Induced</subject><subject>Algorithms</subject><subject>Animals</subject><subject>beta-binomial</subject><subject>Binomial Distribution</subject><subject>binomial mixture</subject><subject>Comparative analysis</subject><subject>complete monotonicity</subject><subject>Computer Simulation</subject><subject>Correlation analysis</subject><subject>Drug-Related Side Effects and Adverse Reactions - embryology</subject><subject>exchangeability</subject><subject>Fetal Death</subject><subject>Likelihood Functions</subject><subject>link function</subject><subject>Markov analysis</subject><subject>Markov Chains</subject><subject>Mice</subject><subject>Models, Statistical</subject><subject>Regression Analysis</subject><subject>Simulation</subject><issn>0277-6715</issn><issn>1097-0258</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2009</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp1kMtKAzEYRoMoWi_gE0hw5WY0l2aSLKVqLVRFrLgMmSRjo3Opk4y2Pr1TOujKVSCc_8B3ADjG6BwjRC6CL89pSsUWGGAkeYIIE9tggAjnScox2wP7IbwhhDEjfBfsYcmGgkg5AOUlbCufe2ehXiyaWps5zOsG6koXq29fvUK3NHNdvTqdFQ5mvtLNClodNfzycb4-KrzR0ddVgLGG1n26ol6Uroq66D6W3vi4giG21rtwCHZyXQR31L8H4Pnmeja6TaYP48nocpoYKphIBElNKiWxueWccIFyQqUhliCLieAWGYmzYYpTm2Uo51hyzXBGMBsSQVlq6QE43Xi7RR-tC1G91W3TTQqKEIqHFHPaQWcbyDR1CI3L1aLxZTdPYaTWWVWXVa2zduhJ72uz0tk_sO_YAckG-PKFW_0rUk-Tu17Y8z5Et_zldfOuUk45Uy_3YzWlaEQfr2aK0x97z5C7</recordid><startdate>20090910</startdate><enddate>20090910</enddate><creator>Dang, Xin</creator><creator>Keeton, Stephine Lena</creator><creator>Peng, Hanxiang</creator><general>John Wiley & Sons, Ltd</general><general>Wiley Subscription Services, Inc</general><scope>BSCLL</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>K9.</scope></search><sort><creationdate>20090910</creationdate><title>A unified approach for analyzing exchangeable binary data with applications to developmental toxicity studies</title><author>Dang, Xin ; Keeton, Stephine Lena ; Peng, Hanxiang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3858-826c6992dfd772780f239c2d20d1287d0c91b4616dbb0f7197a51b215428356d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2009</creationdate><topic>2,4,5-Trichlorophenoxyacetic Acid - adverse effects</topic><topic>Abnormalities, Drug-Induced</topic><topic>Algorithms</topic><topic>Animals</topic><topic>beta-binomial</topic><topic>Binomial Distribution</topic><topic>binomial mixture</topic><topic>Comparative analysis</topic><topic>complete monotonicity</topic><topic>Computer Simulation</topic><topic>Correlation analysis</topic><topic>Drug-Related Side Effects and Adverse Reactions - embryology</topic><topic>exchangeability</topic><topic>Fetal Death</topic><topic>Likelihood Functions</topic><topic>link function</topic><topic>Markov analysis</topic><topic>Markov Chains</topic><topic>Mice</topic><topic>Models, Statistical</topic><topic>Regression Analysis</topic><topic>Simulation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Dang, Xin</creatorcontrib><creatorcontrib>Keeton, Stephine Lena</creatorcontrib><creatorcontrib>Peng, Hanxiang</creatorcontrib><collection>Istex</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><jtitle>Statistics in medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Dang, Xin</au><au>Keeton, Stephine Lena</au><au>Peng, Hanxiang</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A unified approach for analyzing exchangeable binary data with applications to developmental toxicity studies</atitle><jtitle>Statistics in medicine</jtitle><addtitle>Statist. 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| subjects | 2,4,5-Trichlorophenoxyacetic Acid - adverse effects Abnormalities, Drug-Induced Algorithms Animals beta-binomial Binomial Distribution binomial mixture Comparative analysis complete monotonicity Computer Simulation Correlation analysis Drug-Related Side Effects and Adverse Reactions - embryology exchangeability Fetal Death Likelihood Functions link function Markov analysis Markov Chains Mice Models, Statistical Regression Analysis Simulation |
| title | A unified approach for analyzing exchangeable binary data with applications to developmental toxicity studies |
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