Bayesian inference for disease prevalence using negative binomial group testing |
| |
Authors: | Pritchard Nicholas A Tebbs Joshua M |
| |
Institution: | Department of Mathematics and Statistics, Coastal Carolina University, Conway, SC 29528, USA. |
| |
Abstract: | Group testing, also known as pooled testing, and inverse sampling are both widely used methods of data collection when the goal is to estimate a small proportion. Taking a Bayesian approach, we consider the new problem of estimating disease prevalence from group testing when inverse (negative binomial) sampling is used. Using different distributions to incorporate prior knowledge of disease incidence and different loss functions, we derive closed form expressions for posterior distributions and resulting point and credible interval estimators. We then evaluate our new estimators, on Bayesian and classical grounds, and apply our methods to a West Nile Virus data set. |
| |
Keywords: | Bayesian estimation Inverse sampling Maximum likelihood Pooled testing West Nile Virus |
本文献已被 PubMed 等数据库收录! |
|