Resources

Here is a running list of resources that I have found helpful in my research and teaching:

 

Teaching:

TeachPsych Project Syllabus – syllabi that are peer-reviewed within Psychology

NYU syllabus for Graduate seminar on writing grants, reviewing papers, mentoring, etc.

Recommendations for including more women and people of color in Intro Cog Psych assignments

Recommendations for nixing textbooks for Intro Psych courses in favor of other materials

Freedom app to reduce technological distraction in the classroom

Some advice from the PsychOne conference & Elon U’s Teaching & Learning conference

A workshop on how to teach yourself programming

Resources on how to teach a course on the Reproducibility crisis in Psychology

 

Coding:

Run Python locally in the browser & interact w/ JavaScript via pyodide [demo here]

Convolutional neural nets course from Ariel Rokem on DataCamp

Resting state HRF toolboxes (Python, Matlab, SPM)

Best practices for RMarkdown notebooks

Intro to MNE Python with links to a Docker

Shiny APP for power analysis involving multilevel logistic regression

Regularizing FIR models with canonical HRF (fMRI regression with informed priors)

Neurohackademy resources (lectures, tutorials, & code)

Using RMarkdown for paper writing tutorial

Matlab to Python migration guide

Automatically creating a docker from Github repository

Machine Learning tutorials, part I, part II, part III

Color conversion module in Python

Grouped stats package in R

Making Matlab code verifiably correct

Efficient R programming textbook (free, open source)

Code for regression and correlation Bayesian analysis

Making your own website using the blogdown package in R

Neurolearn, a package that does machine learning on neurovault data

Eight best practices for writing code

fMRIPrep

 

Statistics:

Controlling for confounds & an accompanying blog post

A visual explanation of mixed effects modeling

Using gganimate to generate plots that illustrate how pseudo-correlations can arise, part I and part II

Partitioning variance in meta-analysis

 

Research:

What is a mental disorder? & Problems with measuring depression

 

Data Visualization:

A set of useful posts compiled by other folks

Raincloud plots with code in R, Python, and Matlab (also here for Matlab)

Estimation plots to visualize differences between groups

Overview of different types of visualization plots

GGridges in R to visualize changes to distributions over time

 

Advice from Other Researchers:

A start-up document on resources this researcher wishes he had when he was a student

Advice to your younger self in academia from a host of researchers

Grant writing advice thread

Advice to graduate students

Add your master’s thesis to thesis commons to get indexed

 

Databases:

Microsoft open databases

 

Other:

A list of women and gender minorities in computational cognitive science

Preregistration template

 

To look at & categorize later:

Crowd-sourcing teaching Python sources at this twitter thread

https://github.com/IndrajeetPatil/ggstatsplot

https://www.ucl.ac.uk/pals/research/experimental-psychology/blog/tms-cognitive-neuroscience-workshops/

https://www.sciencedirect.com/science/article/pii/S0092656613000858

https://osf.io/82dsj/

http://shinyapps.org/apps/RGraphCompendium/index.php?utm_content=bufferb2277&utm_medium=social&utm_source=twitter.com&utm_campaign=buffer

http://www.cns.nyu.edu/malab/applying.html

https://osf.io/93znh/