Estimation of interaction effects using pooled biospecimens in a case-control study.

ABSTRACT: Pooling, or physically mixing biospecimens, prior to evaluating biomarkers dramatically reduces biomarker evaluation cost, reduces the quantity of biospecimens required of each individual, and may reduce the percentage of laboratory measurements below the lower limit of detection. Motivated by a case-control study on miscarriage (binary outcome) and cytokines (continuous exposures), we are interested in estimating parameters in a logistic regression, where individuals with the same disease status (with or without a miscarriage) are paired and their pooled cytokine concentrations are assessed. Previous research has proposed a set-based logistic model to evaluate the relationship between a disease and pooled exposures. While the set-based logistic model is very useful for estimating main eff

SUBMITTER: Danaher MR 

PROVIDER: S-EPMC4821703 | biostudies-literature | 2016 Apr

REPOSITORIES: biostudies-literature