Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
In ophthalmological and otolaryngology studies, measurements obtained from both organs (e.g., eyes or ears) of an individual are often highly correlated. Ignoring the intraclass correlation between paired measurements may yield biased inferences. In this article, four different confidence interval (CI) construction methods (maximum likelihood estimates based Wald-type CI, profile likelihood CI, asymptotic score CI and an existing method adjusted for correlated bilateral data) are applied to this type of correlated bilateral data to construct CI for proportion ratio, taking the intraclass correlation into consideration. The coverage probabilities and widths of the resulting CIs are compared with each other in a Monte Carlo simulation study to evaluate their performances. A real dataset from an ophthalmologic study is used to illustrate our methodology.
Download full-text PDF |
Source |
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http://dx.doi.org/10.1080/10543406.2019.1584629 | DOI Listing |
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