{"id":879,"date":"2020-08-21T10:31:30","date_gmt":"2020-08-21T10:31:30","guid":{"rendered":"http:\/\/jsr.isrt.ac.bd\/?post_type=article&#038;p=879"},"modified":"2020-09-14T09:27:26","modified_gmt":"2020-09-14T09:27:26","slug":"54n1_2","status":"publish","type":"article","link":"http:\/\/jsr.isrt.ac.bd\/article\/54n1_2\/","title":{"rendered":"Marginal models for longitudinal count data with dropout"},"content":{"rendered":"<p>In this article, we investigate marginal models for analyzing incomplete longitudinal count data with dropouts. Speci\ufb01cally, we explore commonly used generalized estimating equations and weighted generalized estimating equations for \ufb01tting log-linear models to count data in the presence of monotone missing responses. A series of simulations were carried out to examine the \ufb01nite-sample properties of the estimators in the presence of both correctly speci\ufb01ed and misspeci\ufb01ed dropout mechanisms. An application is provided using actual longitudinal survey data from the Health and Retirement Study (HRS) (HRS, 2019).<\/p>\n<p><a href=\"http:\/\/jsr.isrt.ac.bd\/wp-content\/uploads\/54n1_2.pdf\">Fulltext; <\/a><a href=\"https:\/\/doi.org\/10.47302\/jsr.2020540102\">https:\/\/doi.org\/10.47302\/jsr.2020540102<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>In this article, we investigate marginal models for analyzing incomplete longitudinal count data with dropouts. Speci\ufb01cally, we explore commonly used generalized estimating equations and weighted generalized estimating equations for \ufb01tting log-linear models to count data in the presence of monotone missing responses. A series of simulations were carried out to examine the \ufb01nite-sample properties of [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":0,"menu_order":0,"comment_status":"closed","ping_status":"open","template":"","format":"standard","meta":{"_mi_skip_tracking":false,"_exactmetrics_sitenote_active":false,"_exactmetrics_sitenote_note":"","_exactmetrics_sitenote_category":0,"footnotes":""},"issuem_issue":[27],"issuem_issue_categories":[],"issuem_issue_tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v22.7 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Marginal models for longitudinal count data with dropout - JSR<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/jsr.isrt.ac.bd\/article\/54n1_2\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Marginal models for longitudinal count data with dropout - JSR\" \/>\n<meta property=\"og:description\" content=\"In this article, we investigate marginal models for analyzing incomplete longitudinal count data with dropouts. Speci\ufb01cally, we explore commonly used generalized estimating equations and weighted generalized estimating equations for \ufb01tting log-linear models to count data in the presence of monotone missing responses. A series of simulations were carried out to examine the \ufb01nite-sample properties of [&hellip;]\" \/>\n<meta property=\"og:url\" content=\"https:\/\/jsr.isrt.ac.bd\/article\/54n1_2\/\" \/>\n<meta property=\"og:site_name\" content=\"JSR\" \/>\n<meta property=\"article:modified_time\" content=\"2020-09-14T09:27:26+00:00\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/jsr.isrt.ac.bd\/article\/54n1_2\/\",\"url\":\"https:\/\/jsr.isrt.ac.bd\/article\/54n1_2\/\",\"name\":\"Marginal models for longitudinal count data with dropout - JSR\",\"isPartOf\":{\"@id\":\"https:\/\/jsr.isrt.ac.bd\/#website\"},\"datePublished\":\"2020-08-21T10:31:30+00:00\",\"dateModified\":\"2020-09-14T09:27:26+00:00\",\"breadcrumb\":{\"@id\":\"https:\/\/jsr.isrt.ac.bd\/article\/54n1_2\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/jsr.isrt.ac.bd\/article\/54n1_2\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/jsr.isrt.ac.bd\/article\/54n1_2\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\/\/jsr.isrt.ac.bd\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Articles\",\"item\":\"https:\/\/jsr.isrt.ac.bd\/article\/\"},{\"@type\":\"ListItem\",\"position\":3,\"name\":\"Marginal models for longitudinal count data with dropout\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/jsr.isrt.ac.bd\/#website\",\"url\":\"https:\/\/jsr.isrt.ac.bd\/\",\"name\":\"JSR\",\"description\":\"Journal of Statistical Research\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/jsr.isrt.ac.bd\/?s={search_term_string}\"},\"query-input\":\"required name=search_term_string\"}],\"inLanguage\":\"en-US\"}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Marginal models for longitudinal count data with dropout - JSR","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/jsr.isrt.ac.bd\/article\/54n1_2\/","og_locale":"en_US","og_type":"article","og_title":"Marginal models for longitudinal count data with dropout - JSR","og_description":"In this article, we investigate marginal models for analyzing incomplete longitudinal count data with dropouts. Speci\ufb01cally, we explore commonly used generalized estimating equations and weighted generalized estimating equations for \ufb01tting log-linear models to count data in the presence of monotone missing responses. A series of simulations were carried out to examine the \ufb01nite-sample properties of [&hellip;]","og_url":"https:\/\/jsr.isrt.ac.bd\/article\/54n1_2\/","og_site_name":"JSR","article_modified_time":"2020-09-14T09:27:26+00:00","twitter_card":"summary_large_image","schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"WebPage","@id":"https:\/\/jsr.isrt.ac.bd\/article\/54n1_2\/","url":"https:\/\/jsr.isrt.ac.bd\/article\/54n1_2\/","name":"Marginal models for longitudinal count data with dropout - JSR","isPartOf":{"@id":"https:\/\/jsr.isrt.ac.bd\/#website"},"datePublished":"2020-08-21T10:31:30+00:00","dateModified":"2020-09-14T09:27:26+00:00","breadcrumb":{"@id":"https:\/\/jsr.isrt.ac.bd\/article\/54n1_2\/#breadcrumb"},"inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/jsr.isrt.ac.bd\/article\/54n1_2\/"]}]},{"@type":"BreadcrumbList","@id":"https:\/\/jsr.isrt.ac.bd\/article\/54n1_2\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/jsr.isrt.ac.bd\/"},{"@type":"ListItem","position":2,"name":"Articles","item":"https:\/\/jsr.isrt.ac.bd\/article\/"},{"@type":"ListItem","position":3,"name":"Marginal models for longitudinal count data with dropout"}]},{"@type":"WebSite","@id":"https:\/\/jsr.isrt.ac.bd\/#website","url":"https:\/\/jsr.isrt.ac.bd\/","name":"JSR","description":"Journal of Statistical Research","potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/jsr.isrt.ac.bd\/?s={search_term_string}"},"query-input":"required name=search_term_string"}],"inLanguage":"en-US"}]}},"jetpack_sharing_enabled":true,"_links":{"self":[{"href":"http:\/\/jsr.isrt.ac.bd\/wp-json\/wp\/v2\/article\/879"}],"collection":[{"href":"http:\/\/jsr.isrt.ac.bd\/wp-json\/wp\/v2\/article"}],"about":[{"href":"http:\/\/jsr.isrt.ac.bd\/wp-json\/wp\/v2\/types\/article"}],"author":[{"embeddable":true,"href":"http:\/\/jsr.isrt.ac.bd\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"http:\/\/jsr.isrt.ac.bd\/wp-json\/wp\/v2\/comments?post=879"}],"version-history":[{"count":0,"href":"http:\/\/jsr.isrt.ac.bd\/wp-json\/wp\/v2\/article\/879\/revisions"}],"wp:attachment":[{"href":"http:\/\/jsr.isrt.ac.bd\/wp-json\/wp\/v2\/media?parent=879"}],"wp:term":[{"taxonomy":"issuem_issue","embeddable":true,"href":"http:\/\/jsr.isrt.ac.bd\/wp-json\/wp\/v2\/issuem_issue?post=879"},{"taxonomy":"issuem_issue_categories","embeddable":true,"href":"http:\/\/jsr.isrt.ac.bd\/wp-json\/wp\/v2\/issuem_issue_categories?post=879"},{"taxonomy":"issuem_issue_tags","embeddable":true,"href":"http:\/\/jsr.isrt.ac.bd\/wp-json\/wp\/v2\/issuem_issue_tags?post=879"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}