Awareness of and potential for dependent error in the observational epidemiologic literature: A review
Measurement error discussions often assume classification errors of key variables are independent. Yet, small amounts of dependent error can create large biases in effect estimates. The purpose of this review was to evaluate frequency of measurement error discussions and potential for dependent erro...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Ranker, Lynsie R. [verfasserIn] |
|---|
| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2019 |
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| Schlagwörter: |
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| Umfang: |
178 |
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| Übergeordnetes Werk: |
Enthalten in: Cretaceous tectonic evolution of South China: A preliminary synthesis - Li, Jianhua ELSEVIER, 2014transfer abstract, Amsterdam [u.a.] |
|---|---|
| Übergeordnetes Werk: |
volume:36 ; year:2019 ; pages:15-192 ; extent:178 |
| Links: |
|---|
| DOI / URN: |
10.1016/j.annepidem.2019.06.001 |
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Measurement error discussions often assume classification errors of key variables are independent. Yet, small amounts of dependent error can create large biases in effect estimates. The purpose of this review was to evaluate frequency of measurement error discussions and potential for dependent error in the observational literature. |
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Measurement error discussions often assume classification errors of key variables are independent. Yet, small amounts of dependent error can create large biases in effect estimates. The purpose of this review was to evaluate frequency of measurement error discussions and potential for dependent error in the observational literature. |
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