# testassay

An R package to facilitate assay validation in a hypothesis testing
framework. This is a companion to the following paper:

Michael P Fay, Michael C Sachs, and Kazutoyo Miura. *A Hypothesis
Testing Framework for Validating an Assay for Precision*. (2018),
Statistics in Medicine, 37(4):519-529.

### Abstract

A common way of validating a biological assay for is through a
procedure, where m levels of an analyte are measured with n replicates
at each level, and if all m estimates of the coefficient of variation
(CV) are less than some prespecified level, then the assay is declared
validated for precision within the range of the m analyte levels. Two
limitations of this procedure are: there is no clear statistical
statement of precision upon passing, and it is unclear how to modify the
procedure for assays with constant standard deviation. We provide tools
to convert such a procedure into a set of m hypothesis tests. This
reframing motivates the m:n:q procedure, which upon completion delivers
a 100q% upper confidence limit on the CV. Additionally, for a
post-validation assay output of y, the method gives an ``effective
standard deviation intervalâ€™â€™ of log(y) plus or minus r, which is a 68%
confidence interval on log(mu), where mu is the expected value of the
assay output for that sample. Further, the m:n:q procedure can be
straightfowardly applied to constant standard deviation assays. We
illustrate these tools by applying them to a growth inhibition
assay.

### Details

Read the vignette to see how the package is used https://sachsmc.github.io/testassay. You are welcome to
send us feedback using Github
issues.