P-values: What they are and what they are not, will look in detail at good examples of using p-values and how to interpret them. After reviewing widely understood problems with p-values, attention is drawn to regularly encountered use of p-values where it is less clear what their correct interpretation actually is. Furthermore, we demonstrate why… Read More
The positive and negative predictive values of a dignostic test depend not only on its sensitivity and specificity, but also the prevalence of the disease (or the pre-test probability of disease). This interactive display illustrates that inter-dependence. Move the sensitivity, specificity, and disease prevalence sliders, and watch the positive and negative predictive value sliders change… Read More
If you’re an avid SAS user, you’re likely very familiar with SAS macros. SAS macros are a key component to creating efficient and concise code. Although you cannot use macros in R, R offers other features like functions and loops that can perform the same tasks as SAS macros. Using apply() to loop over variables… Read More
This is a short comparison of SAS and R code in the context of generating multiple datasets. In this example, the mpg dataset from R is used to show how one might use a SAS Macro to subset the data by car class, followed by the R equivalent. You will see that in SAS, the macro… Read More
Researchers at the University of Tennessee Health Science Center (UTHSC) and the Memphis Veterans Affairs (VA) Medical Center were part of the SPRINT MIND (Systolic Blood Pressure Intervention Trial Memory and Cognition IN Decreased Hypertension) multisite clinical trial, which released study findings today showing that intensive lowering of blood pressure reduced the risk of… Read More
This is a practical how-to guide on best practices for debugging code in Julia using the Gallium package. We explore two methods: REPL and Juno-Atom. Installation To use the debugger Gallium in Julia 0.6+, the following packages should be installed: Gallium and ASTInterpreter2. julia> Pkg.add(“Gallium”) julia> Pkg.clone(“https://github.com/Keno/DebuggerFramework.jl”) julia> Pkg.clone(“https://github.com/Keno/ASTInterpreter2.jl”) There are two possible ways to debug with Gallium,… Read More
This is a quick guide on the recommended SAS setup for UT users. This is excerpted from a longer guide on software setup and windows 10. SAS 9.4 TSIM3 Large (16GB) download from UT Knoxville This download will take several hours due to its size (zipped file 16GB). You may want to ask the Biostatistics… Read More
An entertaining look at floating point computation and absurdities that you might encounter if you are not careful. The video is entertaining; the details are in the article. Computers were originally conceived as devices for performing mathematics. The earliest computers spent most of their time solving equations. Although the engineering and scientific community now forms… Read More
Starting from Julia 0.7, missing values are represented using the new missing object. Resulting from intense design discussions, experimentations and language improvements developed over several years, it is the heir of the NA value implemented in the DataArrays package, which used to be the standard way of representing missing data in Julia.
More than half a century of research in theoretical computer science has brought us a great wealth of advanced algorithmic techniques. These techniques can be combined in a variety of ways to provide us with sophisticated, often beautifully elegant algorithms. This diversity of methods is truly stimulating and intellectually satisfying. But is it also necessary?
