Efficient Design and Analysis of Biospecimens with Measurements Subject to Detection Limit

Pooling biospecimens is a well accepted sampling strategy in biomedical research to reduce study cost of measuring biomarkers, and has been shown in the case of normally distributed data to yield more efficient estimation. In this paper we examine the efficiency of pooling, in the context of information matrix related to estimators of unknown parameters, when the biospecimens being pooled yield incomplete observations due to the instruments' limit of detection. Our investigation of three sampling strategies shows that, for a range of values of the detection limit, pooling is the most efficient sampling procedure. For certain other values of the detection limit, pooling can perform poorly.