A method to automate probabilistic sensitivity analyses of misclassified binary variables
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Quantifying and adjusting for disease misclassification due to loss to follow-up in historical cohort mortality studiesBias in logistic regression due to imperfect diagnostic test results and practical correction approachesSpecifying exposure classification parameters for sensitivity analysis: family breast cancer historyIncorporating individual-level distributions of exposure error in epidemiologic analyses: an example using arsenic in drinking water and bladder cancerStudy of Cardiovascular Health Outcomes in the Era of Claims Data: The Cardiovascular Health StudyScreening of healthcare workers for tuberculosis: development and validation of a new health economic model to inform practiceMultiple-bias analysis as a technique to address systematic error in measures of abortion-related mortalityPrenatal influenza exposure and cardiovascular events in adulthood.Validity of birth certificate-derived maternal weight data.Validity of maternal and infant outcomes within nationwide Medicaid data.Comparison of bias analysis strategies applied to a large data setStatistical analysis with missing exposure data measured by proxy respondents: a misclassification problem within a missing-data problem.Validity of birth certificate-derived maternal weight data in twin pregnancies.Misclassification in administrative claims data: quantifying the impact on treatment effect estimates.Antidepressant use in pregnancy and the risk of cardiac defectsPhysical activity, cognitive decline, and risk of dementia: 28 year follow-up of Whitehall II cohort study.Probabilistic approaches to better quantifying the results of epidemiologic studiesValidation data-based adjustments for outcome misclassification in logistic regression: an illustrationThe impact of exposure misclassification on associations between prepregnancy BMI and adverse pregnancy outcomesMedical databases in studies of drug teratogenicity: methodological issuesAntidepressant use and risk for preeclampsia.In utero exposure to tobacco smoke and subsequent reduced fertility in females.Increased risk of orofacial clefts associated with maternal obesity: case-control study and Monte Carlo-based bias analysis.Statistical adjustment of genotyping error in a case-control study of childhood leukaemia.Use of self-reported height and weight biases the body mass index-mortality association.Sensitivity analysis for misclassification in logistic regression via likelihood methods and predictive value weighting.Accuracy of maternal recall of gestational weight gain 4 to 12 years after deliveryNo association between maternal pre-pregnancy obesity and risk of hypospadias or cryptorchidism in male newbornsDevelopment of a claims-based algorithm to identify colorectal cancer recurrence.Extended Matrix and Inverse Matrix Methods Utilizing Internal Validation Data When Both Disease and Exposure Status Are MisclassifiedBinary regression with differentially misclassified response and exposure variables.Is probabilistic bias analysis approximately Bayesian?Potential sensitivity of bias analysis results to incorrect assumptions of nondifferential or differential binary exposure misclassificationSelf-report versus ultrasound measurement of uterine fibroid status.Impact of GOS misclassification on ordinal outcome analysis of traumatic brain injury clinical trialsVitamin D and uterine leiomyoma among a sample of US women: Findings from NHANES, 2001-2006.Low-dose nonlinear effects of smoking on coronary heart disease risk.Predictors of recall certainty of dates of analgesic medication use in pregnancy.Maternal Recall Error in Retrospectively Reported Time-to-Pregnancy: an Assessment and Bias Analysis.A comparison of sensitivity-specificity imputation, direct imputation and fully Bayesian analysis to adjust for exposure misclassification when validation data are unavailable.
P2860
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P2860
A method to automate probabilistic sensitivity analyses of misclassified binary variables
description
im September 2005 veröffentlichter wissenschaftlicher Artikel
@de
wetenschappelijk artikel
@nl
наукова стаття, опублікована у вересні 2005
@uk
name
A method to automate probabilistic sensitivity analyses of misclassified binary variables
@en
A method to automate probabilistic sensitivity analyses of misclassified binary variables
@nl
type
label
A method to automate probabilistic sensitivity analyses of misclassified binary variables
@en
A method to automate probabilistic sensitivity analyses of misclassified binary variables
@nl
prefLabel
A method to automate probabilistic sensitivity analyses of misclassified binary variables
@en
A method to automate probabilistic sensitivity analyses of misclassified binary variables
@nl
P356
P1476
A method to automate probabilistic sensitivity analyses of misclassified binary variables
@en
P2093
Sander Greenland
Timothy L Lash
P304
P356
10.1093/IJE/DYI184
P577
2005-09-19T00:00:00Z