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Published in 2019 at "Pharmacoepidemiology and Drug Safety"
DOI: 10.1002/pds.4701
Abstract: Misclassification of a binary outcome can introduce bias in estimation of the oddsâratio associated with an exposure of interest in pharmacoepidemiology research. It has been previously demonstrated that utilizing information from an internal randomly selected…
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Keywords:
misclassification;
conditional validation;
estimation;
binary outcome ... See more keywords
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Published in 2023 at "Pharmacoepidemiology and Drug Safety"
DOI: 10.1002/pds.5601
Abstract: Key Points 1. Outcome validation is often requested by regulators to address misclassification bias in database studies of drug safety and comparative effectiveness. 2. Validation studies commonly report only one positive predictive value (PPV) estimate.…
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Keywords:
misclassification bias;
misclassification;
validation;
outcome misclassification ... See more keywords
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Published in 2019 at "Statistics in medicine"
DOI: 10.1002/sim.8364
Abstract: New treatments that are noninferior or equivalent to-but not necessarily superior to-the reference treatment may still be beneficial to patients because they have fewer side effects, are more convenient, take less time, or cost less.…
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Keywords:
noninferiority testing;
misclassification;
testing matched;
matched pair ... See more keywords
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Published in 2019 at "Statistics in medicine"
DOI: 10.1002/sim.8370
Abstract: A two-stage enrichment design is a type of adaptive design, which extends a stratified design with a futility analysis on the marker negative cohort at the first stage, and the second stage can be either…
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Keywords:
two stage;
misclassification;
stage enrichment;
marker ... See more keywords
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Published in 2019 at "Statistics in medicine"
DOI: 10.1002/sim.8380
Abstract: Misclassification of outcomes or event types is common in health sciences research and can lead to serious bias when estimating the cumulative incidence functions in settings with competing risks. Recent work has shown how to…
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Keywords:
misclassification;
outcome misclassification;
external validation;
cumulative incidence ... See more keywords
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Published in 2019 at "European Journal of Epidemiology"
DOI: 10.1007/s10654-019-00581-8
Abstract: In clinical epidemiology, the association between a risk factor and a disease can be flawed by bias and confounding. This should be prevented by a proper design and adjustment. One important aspect is the reliability…
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Keywords:
use;
interview;
misclassification;
exposure ... See more keywords
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Published in 2021 at "Scientometrics"
DOI: 10.1007/s11192-020-03789-8
Abstract: Exploring the production of knowledge with quantitative methods is the foundation of scientometrics. In an application of machine learning to scientometrics, we here consider the classification problem of the mapping of academic publications to the…
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Keywords:
machine learning;
misclassification;
scientific disciplines;
academic publications ... See more keywords
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Published in 2017 at "Behaviormetrika"
DOI: 10.1007/s41237-017-0031-y
Abstract: Measurement error in continuous, normally distributed data is well known in the literature. Measurement error in a binary outcome variable, however, remains under-studied. Misclassification is the error in categorical data in which the observed category…
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Keywords:
logistic regression;
misclassification;
regression misclassification;
model ... See more keywords
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Published in 2018 at "Annals of epidemiology"
DOI: 10.1016/j.annepidem.2018.07.011
Abstract: PURPOSE We sought to examine the association between childhood asthma and self-reported maternal smoking during pregnancy (MSDP) after adjusting for a range of exposure misclassification scenarios using a Bayesian approach that incorporated exposure misclassification probability…
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Keywords:
adjusted exposure;
misclassification;
exposure misclassification;
msdp asthma ... See more keywords
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Published in 2020 at "International journal of medical informatics"
DOI: 10.1016/j.ijmedinf.2020.104086
Abstract: BACKGROUND In activity based funding systems, the misclassification of inpatient episode Diagnostic Related Groups (DRGs) can have significant impacts on the revenue of health care providers. Weakly informative Bayesian models can be used to estimate…
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Keywords:
hybrid prior;
detection;
incorporation expert;
expert knowledge ... See more keywords
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Published in 2018 at "Preventive veterinary medicine"
DOI: 10.1016/j.prevetmed.2017.11.010
Abstract: Using imperfect tests may lead to biased estimates of disease frequency and of associations between risk factors and disease. For instance in longitudinal udder health studies, both quarters at risk and incident intramammary infections (IMI)…
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Keywords:
incidence;
misclassification;
quarter;
association ... See more keywords