{"id":377,"date":"2017-05-12T11:06:55","date_gmt":"2017-05-12T11:06:55","guid":{"rendered":"http:\/\/jsr.isrt.ac.bd\/?post_type=article&p=377"},"modified":"2017-05-12T11:07:02","modified_gmt":"2017-05-12T11:07:02","slug":"likelihood-ratio-test-nonignorable-missingness-incomplete-binary-longitudinal-data","status":"publish","type":"article","link":"http:\/\/jsr.isrt.ac.bd\/article\/likelihood-ratio-test-nonignorable-missingness-incomplete-binary-longitudinal-data\/","title":{"rendered":"A likelihood ratio test for nonignorable missingness in incomplete binary longitudinal data"},"content":{"rendered":"

Missing data are common in many clinical studies. When missingness is non-
\nignorable, a full likelihood analysis of the data requires incorporating a missing
\ndata model into the observed data likelihood function. In this article, we study
\nthe bias of the ML estimator when the corresponding maximum likelihood is ob-
\ntained under a misspeci\fed missing data model. We further explore a likelihood
\nratio statistic for testing the missing data mechanism in binary longitudinal data.
\nThe empirical level and power of the test are investigated in small simulations.
\nWe also present an example using some real data obtained from a longitudinal
\nstudy.<\/p>\n

 <\/p>\n

44n1_8<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

Missing data are common in many clinical studies. When missingness is non- ignorable, a full likelihood analysis of the data requires incorporating a missing data model into the observed data likelihood function. In this article, we study the bias of the ML estimator when the corresponding maximum likelihood is ob- tained under a misspeci\fed missing […]<\/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":[11],"issuem_issue_categories":[],"issuem_issue_tags":[],"class_list":["post-377","article","type-article","status-publish","format-standard","hentry","issuem_issue-v44n1"],"yoast_head":"\nA likelihood ratio test for nonignorable missingness in incomplete binary longitudinal data - 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\/likelihood-ratio-test-nonignorable-missingness-incomplete-binary-longitudinal-data\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"A likelihood ratio test for nonignorable missingness in incomplete binary longitudinal data - JSR\" \/>\n<meta property=\"og:description\" content=\"Missing data are common in many clinical studies. When missingness is non- ignorable, a full likelihood analysis of the data requires incorporating a missing data model into the observed data likelihood function. In this article, we study the bias of the ML estimator when the corresponding maximum likelihood is ob- tained under a misspeci ed missing […]\" \/>\n<meta property=\"og:url\" content=\"https:\/\/jsr.isrt.ac.bd\/article\/likelihood-ratio-test-nonignorable-missingness-incomplete-binary-longitudinal-data\/\" \/>\n<meta property=\"og:site_name\" content=\"JSR\" \/>\n<meta property=\"article:modified_time\" content=\"2017-05-12T11:07:02+00:00\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data1\" content=\"1 minute\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/jsr.isrt.ac.bd\/article\/likelihood-ratio-test-nonignorable-missingness-incomplete-binary-longitudinal-data\/\",\"url\":\"https:\/\/jsr.isrt.ac.bd\/article\/likelihood-ratio-test-nonignorable-missingness-incomplete-binary-longitudinal-data\/\",\"name\":\"A likelihood ratio test for nonignorable missingness in incomplete binary longitudinal data - JSR\",\"isPartOf\":{\"@id\":\"https:\/\/jsr.isrt.ac.bd\/#website\"},\"datePublished\":\"2017-05-12T11:06:55+00:00\",\"dateModified\":\"2017-05-12T11:07:02+00:00\",\"breadcrumb\":{\"@id\":\"https:\/\/jsr.isrt.ac.bd\/article\/likelihood-ratio-test-nonignorable-missingness-incomplete-binary-longitudinal-data\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/jsr.isrt.ac.bd\/article\/likelihood-ratio-test-nonignorable-missingness-incomplete-binary-longitudinal-data\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/jsr.isrt.ac.bd\/article\/likelihood-ratio-test-nonignorable-missingness-incomplete-binary-longitudinal-data\/#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\":\"A likelihood ratio test for nonignorable missingness in incomplete binary longitudinal data\"}]},{\"@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":"A likelihood ratio test for nonignorable missingness in incomplete binary longitudinal data - 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\/likelihood-ratio-test-nonignorable-missingness-incomplete-binary-longitudinal-data\/","og_locale":"en_US","og_type":"article","og_title":"A likelihood ratio test for nonignorable missingness in incomplete binary longitudinal data - JSR","og_description":"Missing data are common in many clinical studies. When missingness is non- ignorable, a full likelihood analysis of the data requires incorporating a missing data model into the observed data likelihood function. 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