The effect of misclassification error on risk estimation in case-control studies
Autor(a) principal: | |
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Data de Publicação: | 2015 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Revista brasileira de epidemiologia (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-790X2015000200341 |
Resumo: | INTRODUCTION: In epidemiological studies, misclassification error, especially differential misclassification, has serious implications. OBJECTIVE: To illustrate how differential misclassification error (DME) and non-differential misclassification error (NDME) occur in a case-control design and to describe the trends in DME and NDME. METHODS: Different sensitivity levels, specificity levels, prevalence rates and odds ratios were simulated. Interaction graphics were constructed to study bias in the different settings, and the effect of the different factors on bias was described using linear models. RESULTS: One hundred per cent of the biases caused by NDME were negative. DME biased the association positively more often than it did negatively (70 versus 30%), increasing or decreasing the OR estimate towards the null hypothesis. CONCLUSIONS: The effect of the sensitivity and specificity in classifying exposure, the prevalence of exposure in controls and true OR differed between positive and negative biases. The use of valid exposure classification instruments with high sensitivity and high specificity is recommended to mitigate this type of bias. |
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Revista brasileira de epidemiologia (Online) |
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The effect of misclassification error on risk estimation in case-control studiesClassificationBiasCase-control studiesOdds ratiosSensitivity and specificityComputer Simulation INTRODUCTION: In epidemiological studies, misclassification error, especially differential misclassification, has serious implications. OBJECTIVE: To illustrate how differential misclassification error (DME) and non-differential misclassification error (NDME) occur in a case-control design and to describe the trends in DME and NDME. METHODS: Different sensitivity levels, specificity levels, prevalence rates and odds ratios were simulated. Interaction graphics were constructed to study bias in the different settings, and the effect of the different factors on bias was described using linear models. RESULTS: One hundred per cent of the biases caused by NDME were negative. DME biased the association positively more often than it did negatively (70 versus 30%), increasing or decreasing the OR estimate towards the null hypothesis. CONCLUSIONS: The effect of the sensitivity and specificity in classifying exposure, the prevalence of exposure in controls and true OR differed between positive and negative biases. The use of valid exposure classification instruments with high sensitivity and high specificity is recommended to mitigate this type of bias. Associação Brasileira de Saúde Coletiva2015-06-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-790X2015000200341Revista Brasileira de Epidemiologia v.18 n.2 2015reponame:Revista brasileira de epidemiologia (Online)instname:Associação Brasileira de Saúde Coletiva (ABRASCO)instacron:ABRASCO10.1590/1980-5497201500020005info:eu-repo/semantics/openAccessBaena,ArmandoGarcés-Palacio,Isabel CristinaGrisales,Hugoeng2015-06-09T00:00:00Zoai:scielo:S1415-790X2015000200341Revistahttp://www.scielo.br/rbepidhttps://old.scielo.br/oai/scielo-oai.php||revbrepi@usp.br1980-54971415-790Xopendoar:2015-06-09T00:00Revista brasileira de epidemiologia (Online) - Associação Brasileira de Saúde Coletiva (ABRASCO)false |
dc.title.none.fl_str_mv |
The effect of misclassification error on risk estimation in case-control studies |
title |
The effect of misclassification error on risk estimation in case-control studies |
spellingShingle |
The effect of misclassification error on risk estimation in case-control studies Baena,Armando Classification Bias Case-control studies Odds ratios Sensitivity and specificity Computer Simulation |
title_short |
The effect of misclassification error on risk estimation in case-control studies |
title_full |
The effect of misclassification error on risk estimation in case-control studies |
title_fullStr |
The effect of misclassification error on risk estimation in case-control studies |
title_full_unstemmed |
The effect of misclassification error on risk estimation in case-control studies |
title_sort |
The effect of misclassification error on risk estimation in case-control studies |
author |
Baena,Armando |
author_facet |
Baena,Armando Garcés-Palacio,Isabel Cristina Grisales,Hugo |
author_role |
author |
author2 |
Garcés-Palacio,Isabel Cristina Grisales,Hugo |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Baena,Armando Garcés-Palacio,Isabel Cristina Grisales,Hugo |
dc.subject.por.fl_str_mv |
Classification Bias Case-control studies Odds ratios Sensitivity and specificity Computer Simulation |
topic |
Classification Bias Case-control studies Odds ratios Sensitivity and specificity Computer Simulation |
description |
INTRODUCTION: In epidemiological studies, misclassification error, especially differential misclassification, has serious implications. OBJECTIVE: To illustrate how differential misclassification error (DME) and non-differential misclassification error (NDME) occur in a case-control design and to describe the trends in DME and NDME. METHODS: Different sensitivity levels, specificity levels, prevalence rates and odds ratios were simulated. Interaction graphics were constructed to study bias in the different settings, and the effect of the different factors on bias was described using linear models. RESULTS: One hundred per cent of the biases caused by NDME were negative. DME biased the association positively more often than it did negatively (70 versus 30%), increasing or decreasing the OR estimate towards the null hypothesis. CONCLUSIONS: The effect of the sensitivity and specificity in classifying exposure, the prevalence of exposure in controls and true OR differed between positive and negative biases. The use of valid exposure classification instruments with high sensitivity and high specificity is recommended to mitigate this type of bias. |
publishDate |
2015 |
dc.date.none.fl_str_mv |
2015-06-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-790X2015000200341 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-790X2015000200341 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/1980-5497201500020005 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Associação Brasileira de Saúde Coletiva |
publisher.none.fl_str_mv |
Associação Brasileira de Saúde Coletiva |
dc.source.none.fl_str_mv |
Revista Brasileira de Epidemiologia v.18 n.2 2015 reponame:Revista brasileira de epidemiologia (Online) instname:Associação Brasileira de Saúde Coletiva (ABRASCO) instacron:ABRASCO |
instname_str |
Associação Brasileira de Saúde Coletiva (ABRASCO) |
instacron_str |
ABRASCO |
institution |
ABRASCO |
reponame_str |
Revista brasileira de epidemiologia (Online) |
collection |
Revista brasileira de epidemiologia (Online) |
repository.name.fl_str_mv |
Revista brasileira de epidemiologia (Online) - Associação Brasileira de Saúde Coletiva (ABRASCO) |
repository.mail.fl_str_mv |
||revbrepi@usp.br |
_version_ |
1754212954339803136 |