{"data":{"id":"10.6084/m9.figshare.1568727.v1","type":"dois","attributes":{"doi":"10.6084/m9.figshare.1568727.v1","prefix":"10.6084","suffix":"m9.figshare.1568727.v1","identifiers":[],"alternateIdentifiers":[],"creators":[{"name":"Xiwei Tang","affiliation":[],"nameIdentifiers":[]},{"name":"Qu, Annie","nameType":"Personal","givenName":"Annie","familyName":"Qu","affiliation":[],"nameIdentifiers":[]}],"titles":[{"title":"Mixture Modeling for Longitudinal Data"}],"publisher":"Taylor \u0026 Francis","container":{},"publicationYear":2015,"subjects":[{"subject":"Space Science"},{"subject":"Genetics"},{"subject":"FOS: Biological sciences","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"FOS: Biological sciences","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"Physiology"},{"subject":"Biotechnology"},{"subject":"59999 Environmental Sciences not elsewhere classified","subjectScheme":"FOR"},{"subject":"FOS: Earth and related environmental sciences","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"FOS: Earth and related environmental sciences","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"Immunology"},{"subject":"FOS: Clinical medicine","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"FOS: Clinical medicine","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"69999 Biological Sciences not elsewhere classified","subjectScheme":"FOR"},{"subject":"80699 Information Systems not elsewhere classified","subjectScheme":"FOR"},{"subject":"FOS: Computer and information sciences","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"FOS: Computer and information sciences","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"19999 Mathematical Sciences not elsewhere classified","subjectScheme":"FOR"},{"subject":"FOS: Mathematics","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"FOS: Mathematics","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"Inorganic Chemistry"},{"subject":"FOS: Chemical sciences","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"FOS: Chemical sciences","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"Plant Biology"}],"contributors":[],"dates":[{"date":"2015-09-22","dateType":"Created"},{"date":"2016-11-10","dateType":"Updated"},{"date":"2015","dateType":"Issued"}],"language":null,"types":{"ris":"DATA","bibtex":"misc","citeproc":"dataset","schemaOrg":"Dataset","resourceType":"Dataset","resourceTypeGeneral":"Dataset"},"relatedIdentifiers":[{"relationType":"IsSupplementTo","relatedIdentifier":"10.1080/10618600.2015.1092979","relatedIdentifierType":"DOI"},{"relationType":"IsIdenticalTo","relatedIdentifier":"10.6084/m9.figshare.1568727","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":["201913 Bytes"],"formats":[],"version":null,"rightsList":[{"rights":"Creative Commons Attribution 4.0 International","rightsUri":"https://creativecommons.org/licenses/by/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc-by-4.0","rightsIdentifierScheme":"SPDX"}],"descriptions":[{"description":"In this article, we propose an unbiased estimating equation approach for a two-component mixture model with correlated response data. We adapt the mixture-of-experts model and a generalized linear model for component distribution and mixing proportion, respectively. The new approach only requires marginal distributions of both component densities and latent variables. We use serial correlations from subjects’ subgroup memberships, which improves estimation efficiency and classification accuracy, and show that estimation consistency does not depend on the choice of the working correlation matrix. The proposed estimating equation is solved by an expectation-estimating-equation (EEE) algorithm. In the E-step of the EEE algorithm, we propose a joint imputation based on the conditional linear property for the multivariate Bernoulli distribution. In addition, we establish asymptotic properties for the proposed estimators and the convergence property using the EEE algorithm. Our method is compared to an existing competitive mixture model approach in both simulation studies and an election data application. Supplementary materials for this article are available online.","descriptionType":"Abstract"}],"geoLocations":[],"fundingReferences":[],"xml":"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","url":"https://tandf.figshare.com/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