\usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$var\left( {\hat \beta _{GX}} \right) - E(\sigma _{GX}^2)$$\end{document}varβ^GX-E(σGX2) with \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\sigma _{GX}^2$$\end{document}σGX2 the squared standard error of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\hat \beta _{GX}$$\end{document}β^GX. This simple adjustment is sufficiently accurate for the simulation studies. For the analysis of data, we developed an improved version of the simulation extrapolation (SIMEX) algorithm23,24. This is more computationally intensive but also more accurate, and yields confidence intervals for b so that \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$var(\hat b)$$\end{document}var(b^)can be estimated. Details are given in the Methods and Supplementary Note 1.
