CDC STACKS serves as an archival repository of CDC-published products including scientific findings, journal articles, guidelines, recommendations, or other public health information authored or co-authored by CDC or funded partners.
As a repository, CDC STACKS retains documents in their original published format to ensure public access to scientific information.
i
Sensitivity Analyses for Sparse-Data Problems—Using Weakly Informative Bayesian Priors
-
Mar 2013
-
Source: Epidemiology. 2013; 24(2):233-239.
Details:
-
Alternative Title:Epidemiology
-
Personal Author:
-
Description:Sparse-data problems are common, and approaches are needed to evaluate the sensitivity of parameter estimates based on sparse data. We propose a Bayesian approach that uses weakly informative priors to quantify sensitivity of parameters to sparse data. The weakly informative prior is based on accumulated evidence regarding the expected magnitude of relationships using relative measures of disease association. We illustrate the use of weakly informative priors with an example of the association of lifetime alcohol consumption and head and neck cancer. When data are sparse and the observed information is weak, a weakly informative prior will shrink parameter estimates toward the prior mean. Additionally, the example shows that when data are not sparse and the observed information is not weak, a weakly informative prior is not influential. Advancements in implementation of Markov Chain Monte Carlo simulation make this sensitivity analysis easily accessible to the practicing epidemiologist.
-
Subjects:
-
Source:
-
Pubmed ID:23337241
-
Pubmed Central ID:PMC3607322
-
Document Type:
-
Funding:
-
Volume:24
-
Issue:2
-
Collection(s):
-
Main Document Checksum:
-
Download URL:
-
File Type: