Posts

New Methods for EEG Artifact Rejection It’s been a while since we have revised our artifact rejection methods in our pipeline. Our lab primarily uses a semi-automated pipeline with ICA (Extended Infomax) for artifact cleaning of selected components.

A tutorial on generating correlations Introduction and Goals In this tutorial, we will conduct clinical correlations in a large EEG dataset. Our ambitious set of goals includes: Wrangling data into a wide-format for correlation anaysis Conducting bivariate correlations Performing partial correlations Correction for multiple comparisions Visualizing relationships Creating an interactive application for exploring correlations Dataset We have used the auditory chirp dataset in previous tutorials.

Correlation Tutorial: Performing Correlation Analysis If you haven’t prepared data for this tutorial, please see part 1 here. Introduction and Goals In this tutorial, we will conduct clinical correlations in a large EEG dataset.

Introduction In part 1, we used the gtsummary package to create a publication-ready demographics table with a few (relatively!) lines of code. In part 2, we examined the normality of the data to help chose the right statistical test.

Introduction to gtsummary package “The {gtsummary} package provides an elegant and flexible way to create publication-ready analytical and summary tables using the R programming language.” https://www.danieldsjoberg.com/gtsummary/ Introduction I ran across this amazing package on the datascience side of Twitter.

Introduction In part 1, we used the gtsummary package to create a publication-ready demographics table with a few (relatively!) lines of code. In part 2, we will examine the normality of the data to help chose the right statistical test.

Easy workflow for setting up screenshots/GIF on Blog Posts Writing development blogs doesn’t have to be time consuming and can serve as an permanent reference the history of your workflow. I wanted to provide from tips for other data science bloggers that might overall simplify your experience.

Easy Visualization of Correlation Results with R Shiny in 3 Levels: Basic, Publish, and Share The next level: Publish In the last lesson, we built a basic functional version of our correlation viewer application.

Easy Visualization of Correlation Results with R Shiny in 3 Levels: Basic, Publish, and Share Introduction: Basic, Publish, and Share Method It isn’t all that difficult to code R shiny applications if you already know how to program in R.

The “containerization” of software platforms has made quickly setting up a high-performance, reproducible research workflow more feasible. In this tutorial, we will be putting together the pieces on a full research workflow that incorporates multiple analysis platforms, but importantly, tied to the goal of a reproducible academic manuscript.