Recent & Upcoming Talks

2022

ManyFaces: A big team science approach to face perception and recognition

Here we introduce ManyFaces, a recently formed big team science group for face perception and face recognition research. This symposium will introduce the scope and aims of ManyFaces and highlight the work of two of the working groups within ManyFaces: stimulus meta-database and stimulus collection.

2022-10-27 18:15 — 19:15 Online

Thora Bjornsdottir, Lisa DeBruine, Vít Třebický

ManyFaces: A big team science approach to face perception and recognition

Why Code?

In this talk, I summarise the benefits of using code to process and analyse data, give some practical tips for developing your skills, demonstrate how data simulation can improve your research, and discuss the benefits of code review.

2022-09-28 14:00 — 15:00 Lancaster University

Lisa DeBruine

Why Code?

How to set up a big team science project

This asynchronous workshop will introduce the tools and resources for organising communication and information for a new big team science project. The workshop is an online book with Spanish and Turkish translations.

2022-09-23 09:00 — 11:00 https://debruine.github.io/big-team-setup/

Lisa DeBruine

How to set up a big team science project

Data Simulation Workshops

This workshop will cover power analyses across a wide range of statistical tests, including linear mixed models.

2022-04-27 09:00 — 15:00 York University

Lisa DeBruine

Data Simulation Workshops

2021

Everything is cool when you're part of a team

How large-scale collaborations such as the Psychological Science Accelerator can improve both replicability and generalisability.

2021-10-19 16:00 — 17:00 University of York

Lisa DeBruine

Everything is cool when you're part of a team

An ounce of prevention is worth a pound of cure

Things you can do during the planning stage of your project to help you develop healthy research habits.

2021-10-13 15:00 — 16:00 University of Glasgow (Zoom)

Heather Cleland Woods, Phil McAleer, Lisa DeBruine, Kate Reid

Mixed effects models for designs with randomly sampled stimuli

How and why to use linear mixed effects models.

2021-10-05 16:00 — 18:00 Princeton University

Lisa DeBruine

Mixed effects models for designs with randomly sampled stimuli