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In unpaired data analysis the α i cancels out, so it does not contribute to the variance.
However, the second term in the linear estimator at point i cancels the first term in the linear estimator at point i + 1.
Furthermore, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\frac{1}{ 2} cov\left {A}_d,{\overline{A}}_s\right)={F}_i{\sigma}_A^2 $$\end{document}, so that F i cancels from Equation (11).
In this case, we can neglect k-I in (6), δI cancels, and we obtain kdrug ≈ (δpre+kHIV / IC50) m.
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