Resources

This documents collects material supporting the lectures on YouTube.

First lecture

Nosek, 2015: Estimating the reproducibility of psychological science.
Kapur et al., 2012: Why has it taken so long for biological psychiatry to develop clinical tests and what to do about it?

Biau et al., 2010: P value and the theory of hypothesis testing: an explanation for new researchers.
Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations
Simonsohn et al., 2014: P-Curve: A Key to the File-Drawer.
Simons and Simonson 2011: False-Positive Psychology: Undisclosed Flexibility in Data Collection and Analysis Allows Presenting Anything as Significant.
Ioannidis, 2005: Why Most Published Research Findings Are False.

Stack quest: YouTube Channel explaining machine learning topics in an understandable way.

Retraction watch: A website tracking papers that were retracted after publication.

Markdown Guide: Basics about writing markdown files.

Machine Learning Mastery: Primarily for machine learning but has excellent tutorials in python and R.

OHBM Brainhack 2021: Introduction to git and Github.

First Contributions: A project that aims to simplify and guide the way beginners make their first contribution.

Awesome Public Datasets: A set of links to good quality, publicly available datasets.

ReproRehab Git session: Recording from a ReproRehab Git session.

Awesome Reproducible Research: A curated list of reproducible research case studies, projects, tutorials, and media.

The Turing Way - Guide for Reproducible Research: This guide covers topics related to skills, tools and best practices for research reproducibility.

Books:

How to merge the neighborhood atlas with 5 digit zip code data in R
How to merge AQI data from the EPA and merge it with participant zip code in R: github repo with code
How to merge water quality data with individual zip codes: github repo with code
How to merge Food Access Data from the USDA with zip code data in R: github repo with code