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To pool or not to pool, from whether to when: applications of pooling to biospecimens subject to a limit of detection
Author(s) -
Schisterman Enrique F.,
Vexler Albert
Publication year - 2008
Publication title -
paediatric and perinatal epidemiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.667
H-Index - 88
eISSN - 1365-3016
pISSN - 0269-5022
DOI - 10.1111/j.1365-3016.2008.00956.x
Subject(s) - pooling , context (archaeology) , sampling (signal processing) , parametric statistics , limit (mathematics) , sample (material) , monte carlo method , sample size determination , limiting , medicine , statistics , data mining , computer science , econometrics , artificial intelligence , mathematics , mechanical engineering , paleontology , mathematical analysis , chemistry , filter (signal processing) , chromatography , engineering , computer vision , biology
Summary Pooling of biological specimens has been utilised as a cost‐efficient sampling strategy, but cost is not the unique limiting factor in biomarker development and evaluation. We examine the effect of different sampling strategies of biospecimens for exposure assessment that cannot be detected below a detection threshold (DT). The paper compares use of pooled samples to a randomly selected sample from a cohort in order to evaluate the efficiency of parameter estimates. The proposed approach shows that a pooling design is more efficient than a random sample strategy under certain circumstances. Moreover, because pooling minimises the amount of information lost below the DT, the use of pooled data is preferable (in a context of a parametric estimation) to using all available individual measurements, for certain values of the DT. We propose a combined design, which applies pooled and unpooled biospecimens, in order to capture the strengths of the different sampling strategies and overcome instrument limitations (i.e. DT). Several Monte Carlo simulations and an example based on actual biomarker data illustrate the results of the article.