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Statistical design for a small serial dilution series
Author(s) -
Zelterman Daniel,
Tulupyev Alexander,
Heimer Robert,
Abdala Nadia
Publication year - 2009
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.3774
Subject(s) - computer science , series (stratigraphy) , entropy (arrow of time) , statistics , human immunodeficiency virus (hiv) , principle of maximum entropy , optimal design , mathematics , virology , artificial intelligence , medicine , machine learning , biology , paleontology , physics , quantum mechanics
We describe statistical plans for a serial dilution series designed to detect and estimate the number of viral particles in a solution. The design addresses a problem when a very limited number of aliquots are available for proliferation. A gamma prior distribution on the number of viral particles allows us to describe the marginal probability distribution of all experimental outcomes. We examine a design that minimizes the expected reciprocal information and compare this with the maximum entropy design. We argue that the maximum entropy design is more useful from the point of view of the laboratory technician. The problem and design are motivated by our study of the viability of human immunodeficiency virus in syringes and other equipment that might mediate blood‐borne viral transmission. Copyright © 2009 John Wiley & Sons, Ltd.