Multiple Hypothesis Testing in R

Roland Stevenson 2019-10-02

In the first article of this series, we looked at understanding type I and type II errors in the context of an A/B test, and highlighted the issue of “peeking”. In the second, we illustrated a way to calculate always-valid p-values that were immune to peeking. We will now explore multiple hypothesis testing, or what happens when multiple tests are conducted on the same family of data. We will set things up as before, with the false positive rate (\alpha = 0.

August 2019: "Top 40" R packages

Joseph Rickert 2019-09-26

Two hundred and twenty-seven new packages made it to CRAN in August. Quite a few were devoted to medical or genomic applications, and this is reflected in my “Top 40” selections, listed below in nine categories: Computational Methods, Data, Genomics, Machine Learning, Medicine and Pharma, Statistics, Time Series, Utilities, and Visualization. Computational Methods fmcmc v0.2-0: Provides a flexible Markov Chain Monte Carlo (MCMC) framework for implementing Metropolis-Hastings algorithms. Thee is a vignette on user-defined kernels and another on workflows.

Accelerate your plots with ggforce

Edgar Ruiz 2019-09-19

In this post, I will walk you through some examples that show off the major features of the ggforce package. The main goal is to share a few ideas about customizing visualizations that you may find useful in your everyday work. The ggforce package is an extension to ggplot2 developed by Thomas Pedersen. Thanks to ggforce, you can enhance almost any ggplot by highlighting data groupings, and focusing attention on interesting features of the plot.

R/Medicine 2019 Workshops

Joseph Rickert 2019-09-12

R/Medicine 2019 kicked off on Thursday with two outstanding workshops. It was difficult to choose between the two, but fortunately both presenters developed rich sets of materials that are available online. Alison Hill delivered R Markdown for Medicine with an elegant HTML exposition masterfully created to cultivate beginners while still engaging experienced R Markdown users. Photo by Samuel Zeller on Unsplash In four sections: (1) R Markdown Anatomy, (2) Outputs and Tables, (3) Graphics for Communication and (4) Data and Workflows she developed aspects of R Markdown aimed at statisticians and clinicians writing medical document which should also delight a wide audience of R Markdown users.

How to Send Custom E-mails with R

Hadrien Dykiel 2019-09-04

A common business oriented data science task is to programatically craft and send custom emails. In this post, I will show how to accomplish this with R on the RStudio Connect platform (a paid product built for the enterprise) using the blastula package.blastula provides a set of functions for composing high-quality HTML e-mails that render across various e-mail clients, such as gmail and outlook, and also includes tooling for sending out those e-mails via SMTP, the standard protocol for electronic mail transmission between different e-mail providers.

July 2019 "Top 40" R Packages

Joseph Rickert 2019-08-29

One hundred seventy-six new packages made it to CRAN in July. Here are my “Top 40” picks organized into twelve categories: Data, Data Science, Finance, Genomics, Machine Learning, Mathematics, Medicine, Statistics, Time Series, Topological Data Analysis, Utilities and Visualization. Data eia v0.3.2: Provides API access to data from the US Energy Information Administration (EIA). Use of the API requires a free API key. See the Package Overview. litteR v0.4.1: Implements a user interface to analyze litter data: beach litter, riverain litter, floating litter, seafloor litter, etc.

Calculating Always-Valid p-values in R

Roland Stevenson 2019-08-22

In this post, we will develop a framework for always-valid inference based on the paper Always Valid Inference: Continuous Monitoring of A/B Tests (2019 Johari, Pekelis, Walsh). Using an always-valid p-value allows us to continuously monitor A/B tests, and potentially stop the test early in a valid way1. In section 5 of the paper, the authors propose their method for calculating always-valid p-values: the mixture sequential ratio probability test (mSPRT), first introduced by Robbins (1970).

Tech Dividends, Part 2

Jonathan Regenstin 2019-08-17

In a previous post, we explored the dividend history of stocks included in the SP500, and we followed that with exploring the dividend history of some NASDAQ tickers. Today’s post is a short continuation of that tech dividend theme, with the aim of demonstrating how we can take our previous work and use it to quickly visualize research from the real world. In this case, the inspiration is the July 27th edition of Barron’s, which has an article called 8 Tech Stocks That Yield Steady Payouts.

Plumber Logging

James Blair 2019-08-13

The plumber R package is used to expose R functions as API endpoints. Due to plumber’s incredible flexibility, most major API design decisions are left up to the developer. One important consideration to be made when developing APIs is how to log information about API requests and responses. This information can be used to determine how plumber APIs are performing and how they are being utilized. An example of logging API requests in plumber is included in the package documentation.

Tech Dividends, Part 1

Jonathan Regenstein 2019-08-07

In a previous post, we explored the dividend history of stocks included in the SP500. Today, we’ll extend that analysis to cover the Nasdaq because, well, because in the previous post I said I would do that. We’ll also explore a different source for dividend data, do some string cleaning and check out ways to customize a tooltip in plotly. Bonus feature: we’ll get into some animation too.