{"id":277,"date":"2017-03-14T20:10:17","date_gmt":"2017-03-14T20:10:17","guid":{"rendered":"http:\/\/jsr.isrt.ac.bd\/?post_type=article&p=277"},"modified":"2017-03-14T20:10:17","modified_gmt":"2017-03-14T20:10:17","slug":"analysis-error-contaminated-survival-data-proportional-odds-model","status":"publish","type":"article","link":"http:\/\/jsr.isrt.ac.bd\/article\/analysis-error-contaminated-survival-data-proportional-odds-model\/","title":{"rendered":"Analysis of error-contaminated survival data under the proportional odds model"},"content":{"rendered":"

There has been extensive research interest in analysis of survival data with covariates subject
\nto measurement error. The focus of the most discussions is on the proportional hazards
\n(PH) model, although there are some work concerning the accelerated failure time (AFT)
\nmodel and the additive hazards (AH) model. Relatively little attention has been directed to
\nstudying the impact of measurement error on other models, such as the proportional odds
\n(PO) model. The proportional odds model is an important alternative when PH, AFT or
\nAH models are not appropriate to fit data. In this paper we discuss two inference methods
\nto accommodate measurement error effects under the PO model, in contrast to the naive
\nanalysis that ignores the covariate measurement error. Numerical studies are conducted to
\nevaluate the performance of the proposed methods.<\/p>\n

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

There has been extensive research interest in analysis of survival data with covariates subject to measurement error. The focus of the most discussions is on the proportional hazards (PH) model, although there are some work concerning the accelerated failure time (AFT) model and the additive hazards (AH) model. Relatively little attention has been directed to […]<\/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":[8],"issuem_issue_categories":[],"issuem_issue_tags":[],"yoast_head":"\nAnalysis of error-contaminated survival data under the proportional odds model - 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\/analysis-error-contaminated-survival-data-proportional-odds-model\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Analysis of error-contaminated survival data under the proportional odds model - JSR\" \/>\n<meta property=\"og:description\" content=\"There has been extensive research interest in analysis of survival data with covariates subject to measurement error. The focus of the most discussions is on the proportional hazards (PH) model, although there are some work concerning the accelerated failure time (AFT) model and the additive hazards (AH) model. Relatively little attention has been directed to […]\" \/>\n<meta property=\"og:url\" content=\"https:\/\/jsr.isrt.ac.bd\/article\/analysis-error-contaminated-survival-data-proportional-odds-model\/\" \/>\n<meta property=\"og:site_name\" content=\"JSR\" \/>\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\/analysis-error-contaminated-survival-data-proportional-odds-model\/\",\"url\":\"https:\/\/jsr.isrt.ac.bd\/article\/analysis-error-contaminated-survival-data-proportional-odds-model\/\",\"name\":\"Analysis of error-contaminated survival data under the proportional odds model - JSR\",\"isPartOf\":{\"@id\":\"https:\/\/jsr.isrt.ac.bd\/#website\"},\"datePublished\":\"2017-03-14T20:10:17+00:00\",\"dateModified\":\"2017-03-14T20:10:17+00:00\",\"breadcrumb\":{\"@id\":\"https:\/\/jsr.isrt.ac.bd\/article\/analysis-error-contaminated-survival-data-proportional-odds-model\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/jsr.isrt.ac.bd\/article\/analysis-error-contaminated-survival-data-proportional-odds-model\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/jsr.isrt.ac.bd\/article\/analysis-error-contaminated-survival-data-proportional-odds-model\/#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\":\"Analysis of error-contaminated survival data under the proportional odds model\"}]},{\"@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":"Analysis of error-contaminated survival data under the proportional odds model - 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\/analysis-error-contaminated-survival-data-proportional-odds-model\/","og_locale":"en_US","og_type":"article","og_title":"Analysis of error-contaminated survival data under the proportional odds model - JSR","og_description":"There has been extensive research interest in analysis of survival data with covariates subject to measurement error. The focus of the most discussions is on the proportional hazards (PH) model, although there are some work concerning the accelerated failure time (AFT) model and the additive hazards (AH) model. Relatively little attention has been directed to […]","og_url":"https:\/\/jsr.isrt.ac.bd\/article\/analysis-error-contaminated-survival-data-proportional-odds-model\/","og_site_name":"JSR","twitter_card":"summary_large_image","twitter_misc":{"Est. reading time":"1 minute"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"WebPage","@id":"https:\/\/jsr.isrt.ac.bd\/article\/analysis-error-contaminated-survival-data-proportional-odds-model\/","url":"https:\/\/jsr.isrt.ac.bd\/article\/analysis-error-contaminated-survival-data-proportional-odds-model\/","name":"Analysis of error-contaminated survival data under the proportional odds model - JSR","isPartOf":{"@id":"https:\/\/jsr.isrt.ac.bd\/#website"},"datePublished":"2017-03-14T20:10:17+00:00","dateModified":"2017-03-14T20:10:17+00:00","breadcrumb":{"@id":"https:\/\/jsr.isrt.ac.bd\/article\/analysis-error-contaminated-survival-data-proportional-odds-model\/#breadcrumb"},"inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/jsr.isrt.ac.bd\/article\/analysis-error-contaminated-survival-data-proportional-odds-model\/"]}]},{"@type":"BreadcrumbList","@id":"https:\/\/jsr.isrt.ac.bd\/article\/analysis-error-contaminated-survival-data-proportional-odds-model\/#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":"Analysis of error-contaminated survival data under the proportional odds model"}]},{"@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\/277"}],"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=277"}],"version-history":[{"count":0,"href":"http:\/\/jsr.isrt.ac.bd\/wp-json\/wp\/v2\/article\/277\/revisions"}],"wp:attachment":[{"href":"http:\/\/jsr.isrt.ac.bd\/wp-json\/wp\/v2\/media?parent=277"}],"wp:term":[{"taxonomy":"issuem_issue","embeddable":true,"href":"http:\/\/jsr.isrt.ac.bd\/wp-json\/wp\/v2\/issuem_issue?post=277"},{"taxonomy":"issuem_issue_categories","embeddable":true,"href":"http:\/\/jsr.isrt.ac.bd\/wp-json\/wp\/v2\/issuem_issue_categories?post=277"},{"taxonomy":"issuem_issue_tags","embeddable":true,"href":"http:\/\/jsr.isrt.ac.bd\/wp-json\/wp\/v2\/issuem_issue_tags?post=277"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}