AMS 597: Statistical Computing Pei-Fen Kuan (c) Applied Math and Stats, Stony Brook University Pei-Fen Kuan (c) (Applied Math and Stats, Stony Brook University)AMS 597: Statistical Computing 1 / 6 Individual Project Each student will write an R package implementing statistical methods described in the following paper “A Simple and Robust Method for Partially Matched Samples Using the P-Values Pooling Approach”, Stat Med (2013) https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3717400/ The pdf version of this paper is available at Blackboard (see ScientificPaper_ProjectSpring2021.pdf) Pei-Fen Kuan (c) (Applied Math and Stats, Stony Brook University)AMS 597: Statistical Computing 2 / 6 Individual Project This paper discussed several methods for handling partially matched samples E.g., Complete samples Before Trt x1 x2 x3 x4 x5 x6 x7 x8 x9 x10 After Trt y1 y2 y3 y4 y5 y6 y7 y8 y9 y10 Partially matched samples Before Trt x1 x2 NA NA NA x6 x7 x8 x9 x10 After Trt NA NA y3 y4 y5 y6 y7 y8 y9 y10 Pei-Fen Kuan (c) (Applied Math and Stats, Stony Brook University)AMS 597: Statistical Computing 3 / 6 Individual Project You will write function(s) implementing I Liptak’s weighted Z-test I Kim et al.’s modified t-statistic I Looney and Jones’s corrected Z-test I Lin and Stivers’s MLE based test under heteroscedasticity I Ekbohm’s MLE-based test under homoscedasticity You will then wrap these up as an R package Pei-Fen Kuan (c) (Applied Math and Stats, Stony Brook University)AMS 597: Statistical Computing 4 / 6 Individual Project The R package has to be complete and contains a vignette describing how to use the R package The R package is due May 05, 2021 at 5:00 PM Submit your package as original source package (i.e., .tar.gz file) on Blackboard>Assignments>Project. Name your package PMlastname_version.tar.gz (version is generated automatically after you build your package successfully) Some of the grading criteria include: I Can the R package be installed successfully? I Is the R package implementing the required method correctly? I Has it considered all possible scenarios? I Is the R package user friendly (vignette, help files, warning messages, sample data, sample code)? I What is the computational speed? Pei-Fen Kuan (c) (Applied Math and Stats, Stony Brook University)AMS 597: Statistical Computing 5 / 6 Individual Project Some useful links: http://kbroman.org/pkg_primer/ http://kbroman.org/Tools4RR/assets/lectures/08_rpack_ withnotes.pdf https://hilaryparker.com/2014/04/29/ writing-an-r-package-from-scratch/ https://cran.r-project.org/doc/contrib/ Leisch-CreatingPackages.pdf https: //ourcodingclub.github.io/tutorials/writing-r-package/ Pei-Fen Kuan (c) (Applied Math and Stats, Stony Brook University)AMS 597: Statistical Computing 6 / 6
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