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1. pubs.acs.org › doi › pdfProviding the Missing Link: the Exposure Science Ontology ExO

   pubs.acs.org › doi › pdf

   Feb 10, 2012 · The ontology aims to represent the possible spectrum and granularity of data involved in an exposure event or study. The development and use of terminology that is both accepted and widely used by exposure practitioners is critical for integration and future growth of the exposure science field.

   • Author: Carolyn J. Mattingly, Thomas E. McKone, Michael A. Callahan, Judith A. Blake, Elaine A. Cohen Hubal

   • Publish Year: 2012

2. pubs.acs.org › doi › 10Providing the Missing Link: the Exposure Science Ontology ExO

   pubs.acs.org › doi › 10

   ExO is anchored by four major concepts or root classes that were identified by the working group as key to capturing exposure information. These concepts are (1) exposure event, (2) exposure stressor, (3) exposure receptor, and (4) exposure outcome.

   • Author: Carolyn J. Mattingly, Thomas E. McKone, Michael A. Callahan, Judith A. Blake, Elaine A. Cohen Hubal

   • Publish Year: 2012

3. www.researchgate.net › publication › 259248630(PDF) Causal inference with missing exposure information ...

   www.researchgate.net › publication › 259248630

   Dec 5, 2013 · In this article, we describe and compare a collection of methods based on different modeling assumptions, under standard assumptions for missing data (i.e. missing-at-random and positivity)...

4. www.researchgate.net › publication › 221822920Providing the Missing Link: the Exposure Science Ontology ExO

   www.researchgate.net › publication › 221822920

   Feb 10, 2012 · Request full-text PDF. To read the full-text of this research, you can request a copy directly from the authors.

5. www.tandfonline.com › doi › fullFull article: Missing data and multiple imputation in ...

   www.tandfonline.com › doi › full

   Mar 15, 2017 · Missing data are ubiquitous to clinical epidemiological research. Missing data are often categorized into the following three types: MCAR, MAR, and MNAR. For the most part, in clinical epidemiologic research, missing values are neither MCAR nor MNAR but MAR.

6. link.springer.com › chapter › 10Misclassification - SpringerLink

   link.springer.com › chapter › 10

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   Mar 25, 2022 · Misclassification of measures of exposure, disease, and covariates (e.g., confounders, mediators and effect measure modifiers) are widespread in epidemiologic research. Nutritional epidemiology, for example, often relies on food frequency questionnaires to assess nutrient and caloric intake of study participants.

7. People also ask

   What is exposure misclassification?

   • When talking about exposure misclassification, we are typically, though not necessarily, referring to outcome status. To be more precise, if D is the true outcome status, nondifferential misclassification of exposure occurs when both of the following are true: and

   Misclassification - SpringerLink

   link.springer.com/chapter/10.1007/978-3-030-82673-4_6

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   What if the classification of exposure is nondifferential?

   • This implies that if the classification of exposure is nondifferential with respect to the outcome, positive predictive value and negative predictive value will differ between those with and without the disease, if there is an effect of the exposure on the outcome.

   Misclassification - SpringerLink

   link.springer.com/chapter/10.1007/978-3-030-82673-4_6

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   When is nondifferential exposure misclassification expected?

   • Nondifferential exposure misclassification might also be expected when exposure is ascertained after the occurrence of the disease, but the ascertainment scheme relies on information that is independent of disease status.

   Misclassification - SpringerLink

   link.springer.com/chapter/10.1007/978-3-030-82673-4_6

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   How are subjects classified based on exposure status?

   • Along the interior columns, subjects are classified according to their true exposure status (E), while along the interior rows subjects are classified according to their potentially mismeasured status (E *). The equations assume that the participants in the validation study were representative of the study population (e.g., a simple random sample).

   Misclassification - SpringerLink

   link.springer.com/chapter/10.1007/978-3-030-82673-4_6

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   What is missing data in clinical epidemiology?

   • Missing data are ubiquitous in clinical epidemiological research. Individuals with missing data may differ from those with no missing data in terms of the outcome of interest and prognosis in general.

   Full article: Missing data and multiple imputation in clinical

   www.tandfonline.com/doi/full/10.2147/CLEP.S129785

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   How do you calculate exposure misclassification?

   • Let P 1 be the proportion who are observed to be exposed among the diseased and let P 0 be the proportion who are observed to be exposed among the nondiseased. These quantities can be estimated as a/ (a + b) and c/ (c + d) in Table 6.8. A simple formula for the OR bias-adjusted for exposure misclassification is:

   Misclassification - SpringerLink

   link.springer.com/chapter/10.1007/978-3-030-82673-4_6

   See all results for this question

8. www.ncbi.nlm.nih.gov › pmc › articlesNegative Control Exposures: Causal effect Identifiability and ...

   www.ncbi.nlm.nih.gov › pmc › articles

   Nov 11, 2022 · Our specific objectives are to: present and justify conditions sufficient for using a negative control exposure (N) to identify causal effects of an exposure (E) on an outcome (Y) when a confounder (U) is unmeasured; describe probabilistic bias analyses to address confounding that incorporate information from the negative control, c); describe ...