Verification Bias
Sometimes it is not feasible to obtain disease status verification for all study subjects. Analysis of only those with disease ascertainment can result in biased estimates of the accuracy (sensitivity, specificity, ROC curve) of a diagnostic test, screening test, or biomarker if the estimation meth...
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| Format: | Article |
| Language: | English |
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Instituto Nacional de Estatística | Statistics Portugal
2014-04-01
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| Series: | Revstat Statistical Journal |
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| Online Access: | https://revstat.ine.pt/index.php/REVSTAT/article/view/144 |
| _version_ | 1817999424599621632 |
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| author | Todd A. Alonzo |
| author_facet | Todd A. Alonzo |
| author_sort | Todd A. Alonzo |
| collection | DOAJ |
| description |
Sometimes it is not feasible to obtain disease status verification for all study subjects. Analysis of only those with disease ascertainment can result in biased estimates of the accuracy (sensitivity, specificity, ROC curve) of a diagnostic test, screening test, or biomarker if the estimation method does not properly account for the missing disease ascertainment. This paper discusses the impact of this bias, verification bias, when estimating the accuracy of dichotomous and continuous diagnostic tests. In addition, methods to correct for verification bias are described. Areas that require additional attention are also highlighted.
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| first_indexed | 2024-04-14T03:08:47Z |
| format | Article |
| id | doaj.art-d0d62fe49ca746a4a7df8173e635cfef |
| institution | Directory Open Access Journal |
| issn | 1645-6726 2183-0371 |
| language | English |
| last_indexed | 2024-04-14T03:08:47Z |
| publishDate | 2014-04-01 |
| publisher | Instituto Nacional de Estatística | Statistics Portugal |
| record_format | Article |
| series | Revstat Statistical Journal |
| spelling | doaj.art-d0d62fe49ca746a4a7df8173e635cfef2022-12-22T02:15:39ZengInstituto Nacional de Estatística | Statistics PortugalRevstat Statistical Journal1645-67262183-03712014-04-0112110.57805/revstat.v12i1.144Verification BiasTodd A. Alonzo 0University of Southern California Sometimes it is not feasible to obtain disease status verification for all study subjects. Analysis of only those with disease ascertainment can result in biased estimates of the accuracy (sensitivity, specificity, ROC curve) of a diagnostic test, screening test, or biomarker if the estimation method does not properly account for the missing disease ascertainment. This paper discusses the impact of this bias, verification bias, when estimating the accuracy of dichotomous and continuous diagnostic tests. In addition, methods to correct for verification bias are described. Areas that require additional attention are also highlighted. https://revstat.ine.pt/index.php/REVSTAT/article/view/144imputationinverse probability weightingROC curvesensitivityspecificity |
| spellingShingle | Todd A. Alonzo Verification Bias Revstat Statistical Journal imputation inverse probability weighting ROC curve sensitivity specificity |
| title | Verification Bias |
| title_full | Verification Bias |
| title_fullStr | Verification Bias |
| title_full_unstemmed | Verification Bias |
| title_short | Verification Bias |
| title_sort | verification bias |
| topic | imputation inverse probability weighting ROC curve sensitivity specificity |
| url | https://revstat.ine.pt/index.php/REVSTAT/article/view/144 |
| work_keys_str_mv | AT toddaalonzo verificationbias |