Accepted by Scopus and Clarivate Analytics to be indexed in Science Citation Index Expanded, JCR, Current Contents and Biological Abstracts

Statistical analysis of single-copy assays when some observations are zero

Author List
Peter Bacchetti
Ronald Bosch
Eileen Scully
Xutao Deng
Michael Busch
Steven Deeks
Sharon Lewin


Observational and interventional studies for HIV cure research often use single-copy assays to quantify rare entities in blood or tissue samples. Statistical analysis of such measurements presents challenges due to tissue sampling variability and frequent findings of 0 copies in the sample analysed. We examined four approaches to analysing such studies, reflecting different ways of handling observations of 0 copies: (A) replace observations of 0 copies with 1 copy; (B) add 1 to all observed numbers of copies; (C) treat observations of 0 copies as left-censored at 1 copy; and (D) leave the data unaltered and apply a method for count data, negative binomial regression.

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HIV cure research

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