
Statistical analysis of single-copy assays when some observations are zero
Author List |
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Peter Bacchetti |
Ronald Bosch |
Eileen Scully |
Xutao Deng |
Michael Busch |
Steven Deeks |
Sharon Lewin |
Abstract
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.
Published
Article Category
HIV cure research
Article Type
Reviews
Posted Date
19-09-2019