Multiple bias analysis using logistic regression: an example from the National Birth Defects Prevention Study
| Autor: | Penelope P. Howards, D. Kim Waller, W. Dana Flanders, Candice Y. Johnson, Matthew J. Strickland |
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| Rok vydání: | 2018 |
| Předmět: |
Adult
Adolescent Epidemiology media_common.quotation_subject Cleft Lip 030209 endocrinology & metabolism Logistic regression Risk Assessment Article Body Mass Index 03 medical and health sciences Young Adult 0302 clinical medicine Bias Pregnancy Statistics Medicine Humans 030212 general & internal medicine Obesity Selection (genetic algorithm) media_common Selection bias business.industry Confounding Body Weight Pregnancy Outcome Regression analysis Odds ratio Middle Aged Confidence interval Cleft Palate Pregnancy Complications Logistic Models Case-Control Studies Population Surveillance Regression Analysis Female business Body mass index |
| Zdroj: | Annals of epidemiology. 28(8) |
| ISSN: | 1873-2585 |
| Popis: | PURPOSE. Exposure misclassification, selection bias, and confounding are important biases in epidemiologic studies, yet only confounding is routinely addressed quantitatively. We describe how to combine two previously described methods and adjust for multiple biases using logistic regression. METHODS. Weights were created from selection probabilities and predictive values for exposure classification and applied to multivariable logistic regression models in a case-control study of prepregnancy obesity (body mass index ≥30 versus |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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