Confidence intervals for the odds ratio of two independent binomial proportions using data with one type of misclassification

We derive a confidence interval for the odd ratio of two independent binomial proportion parameters with one type of misclassification using an easy-to-implement closed- form algorithm based on the Maximum Likelihood Estimator (MLE) and its asymptotic variance. The model identifiability is obtained...

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Published inJournal of statistics & management systems Vol. 19; no. 2; pp. 259 - 268
Main Authors Rahardja, Dewi, Wu, Han, Huang, Shuguang, Chu, Jianxiong
Format Journal Article
LanguageEnglish
Published New Delhi Taylor & Francis 03.03.2016
Taru Publications
Subjects
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ISSN0972-0510
2169-0014
DOI10.1080/09720510.2015.1047572

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Abstract We derive a confidence interval for the odd ratio of two independent binomial proportion parameters with one type of misclassification using an easy-to-implement closed- form algorithm based on the Maximum Likelihood Estimator (MLE) and its asymptotic variance. The model identifiability is obtained via doubly sampled data. For illustration, we apply our methods to a sudden infant death syndrome (SIDS) dataset.
AbstractList We derive a confidence interval for the odd ratio of two independent binomial proportion parameters with one type of misclassification using an easy-to-implement closed- form algorithm based on the Maximum Likelihood Estimator (MLE) and its asymptotic variance. The model identifiability is obtained via doubly sampled data. For illustration, we apply our methods to a sudden infant death syndrome (SIDS) dataset.
Author Chu, Jianxiong
Wu, Han
Rahardja, Dewi
Huang, Shuguang
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StartPage 259
SubjectTerms Asymptotic properties
Binary data
Confidence intervals
False positive misclassification
Identifiability
Maximum likelihood estimators
Odds ratio
Sampled data
SIDS
Sudden infant death syndrome
Title Confidence intervals for the odds ratio of two independent binomial proportions using data with one type of misclassification
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