{"@context":{"@vocab":"https://cir.nii.ac.jp/schema/1.0/","rdfs":"http://www.w3.org/2000/01/rdf-schema#","dc":"http://purl.org/dc/elements/1.1/","dcterms":"http://purl.org/dc/terms/","foaf":"http://xmlns.com/foaf/0.1/","prism":"http://prismstandard.org/namespaces/basic/2.0/","cinii":"http://ci.nii.ac.jp/ns/1.0/","datacite":"https://schema.datacite.org/meta/kernel-4/","ndl":"http://ndl.go.jp/dcndl/terms/","jpcoar":"https://github.com/JPCOAR/schema/blob/master/2.0/"},"@id":"https://cir.nii.ac.jp/crid/1363388844922780416.json","@type":"Article","productIdentifier":[{"identifier":{"@type":"DOI","@value":"10.1093/pan/mpq025"}},{"identifier":{"@type":"URI","@value":"https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S1047198700012560"}}],"dc:title":[{"@value":"Latent Class Modeling with Covariates: Two Improved Three-Step Approaches"}],"description":[{"type":"abstract","notation":[{"@value":"<jats:p>Researchers using latent class (LC) analysis often proceed using the following three steps: (1) an LC model is built for a set of response variables, (2) subjects are assigned to LCs based on their posterior class membership probabilities, and (3) the association between the assigned class membership and external variables is investigated using simple cross-tabulations or multinomial logistic regression analysis. Bolck, Croon, and Hagenaars (2004) demonstrated that such a three-step approach underestimates the associations between covariates and class membership. They proposed resolving this problem by means of a specific correction method that involves modifying the third step. In this article, I extend the correction method of Bolck, Croon, and Hagenaars by showing that it involves maximizing a weighted log-likelihood function for clustered data. This conceptualization makes it possible to apply the method not only with categorical but also with continuous explanatory variables, to obtain correct tests using complex sampling variance estimation methods, and to implement it in standard software for logistic regression analysis. In addition, a new maximum likelihood (ML)—based correction method is proposed, which is more direct in the sense that it does not require analyzing weighted data. This new three-step ML method can be easily implemented in software for LC analysis. The reported simulation study shows that both correction methods perform very well in the sense that their parameter estimates and their SEs can be trusted, except for situations with very poorly separated classes. The main advantage of the ML method compared with the Bolck, Croon, and Hagenaars approach is that it is much more efficient and almost as efficient as one-step ML estimation.</jats:p>"}]}],"creator":[{"@id":"https://cir.nii.ac.jp/crid/1383388844922780416","@type":"Researcher","foaf:name":[{"@value":"Jeroen K. Vermunt"}]}],"publication":{"publicationIdentifier":[{"@type":"PISSN","@value":"10471987"},{"@type":"EISSN","@value":"14764989"}],"prism:publicationName":[{"@value":"Political Analysis"}],"dc:publisher":[{"@value":"Cambridge University Press (CUP)"}],"prism:publicationDate":"2010","prism:volume":"18","prism:number":"4","prism:startingPage":"450","prism:endingPage":"469"},"reviewed":"false","dc:rights":["https://www.cambridge.org/core/terms"],"url":[{"@id":"https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S1047198700012560"}],"createdAt":"2010-09-23","modifiedAt":"2019-04-27","relatedProduct":[{"@id":"https://cir.nii.ac.jp/crid/1050282677772677120","@type":"Article","resourceType":"学術雑誌論文(journal article)","relationType":["isReferencedBy"],"jpcoar:relatedTitle":[{"@language":"en","@value":"Customer segmentation with purchase channels and media touchpoints using single source panel data"}]},{"@id":"https://cir.nii.ac.jp/crid/1360298757412688640","@type":"Article","resourceType":"学術雑誌論文(journal article)","relationType":["isReferencedBy"],"jpcoar:relatedTitle":[{"@value":"Within-Person Variability Score-Based Causal Inference: A Two-Step Estimation for Joint Effects of Time-Varying Treatments"}]},{"@id":"https://cir.nii.ac.jp/crid/1360567184559919104","@type":"Article","resourceType":"学術雑誌論文(journal article)","relationType":["isReferencedBy"],"jpcoar:relatedTitle":[{"@value":"Identification of neurodevelopmental trajectories in infancy and of risk factors affecting deviant development: a longitudinal birth cohort study"}]},{"@id":"https://cir.nii.ac.jp/crid/1360861705561007232","@type":"Article","resourceType":"学術雑誌論文(journal article)","relationType":["isReferencedBy"],"jpcoar:relatedTitle":[{"@value":"Trajectories of emotional and behavioral problems in school-age children with coordination difficulties and their relationships to ASD/ADHD traits"}]},{"@id":"https://cir.nii.ac.jp/crid/1360865815688732288","@type":"Article","resourceType":"学術雑誌論文(journal article)","relationType":["isReferencedBy"],"jpcoar:relatedTitle":[{"@value":"A model-based clustering algorithm with covariates adjustment and its application to lung cancer stratification"}]},{"@id":"https://cir.nii.ac.jp/crid/1390282763127686784","@type":"Article","resourceType":"学術雑誌論文(journal article)","relationType":["isReferencedBy"],"jpcoar:relatedTitle":[{"@language":"en","@value":"Class Structure and High School Students' Educational Expectations"},{"@language":"ja","@value":"出身階層の資本構造と高校生の進路選択"},{"@language":"ja-Kana","@value":"シュッシン カイソウ ノ シホン コウゾウ ト コウコウセイ ノ シンロ センタク"}]}],"dataSourceIdentifier":[{"@type":"CROSSREF","@value":"10.1093/pan/mpq025"},{"@type":"CROSSREF","@value":"10.4057/jsr.69.21_references_DOI_D85Zaz4t3QsU9J4b1LT58NsB0eu"},{"@type":"CROSSREF","@value":"10.1007/s11336-022-09879-1_references_DOI_D85Zaz4t3QsU9J4b1LT58NsB0eu"},{"@type":"CROSSREF","@value":"10.1093/ije/dyv363_references_DOI_D85Zaz4t3QsU9J4b1LT58NsB0eu"},{"@type":"CROSSREF","@value":"10.1016/j.jretconser.2017.11.012_references_DOI_D85Zaz4t3QsU9J4b1LT58NsB0eu"},{"@type":"CROSSREF","@value":"10.1016/j.ridd.2022.104394_references_DOI_D85Zaz4t3QsU9J4b1LT58NsB0eu"},{"@type":"CROSSREF","@value":"10.1142/s0219720023500191_references_DOI_D85Zaz4t3QsU9J4b1LT58NsB0eu"}]}