HKUEMS :: Event Details

Practical Meta-analysis Workshop
posted by Department of Psychology for HKU and Public
Event Type: Public Lecture/Forum/Seminar/Workshop/Conference/Symposium
Event Nature: Others

Event Details

In this 3-hour workshop, Dr Gilad Feldman will introduce practical procedures, methods, and hands-on tools to conduct high-quality meta-analysis incorporating some of the latest advancements in psychological science and open-science (e.g., meta-analysis pre-registrations, advanced bias estimates with p/z-curves, etc.).

He will demonstrate both experimental and correlational metas and share a bit about some of the meta-analysis projects his students and he completed last year that these can be done well by undergraduates and masters students. He'll be demonstrating meta tools such as Shiny webapps (MAVIS), JAMOVI click-n-run software with the wonderful MAJOR extension, R Markdown code for automated meta-analysis outputs, and METABUS.

Please do bring your laptops, and to save time, try the following before the workshop:
Link for MAVIS (just open it in your browser): http://kylehamilton.net/shiny/MAVIS/

Download and install JAMOVI: https://www.jamovi.org/download.html

MAJOR JAMOVI extension: https://github.com/kylehamilton/MAJOR

Download and install R/RStudio, here's a quick how to video: https://www.youtube.com/watch?v=d-u_7vdag-0

Create an account on METABUS: https://shiny.metabus.org/users/sign-in (official website: http://metabus.org/ )

* R proficiency is NOT a must for this workshop, it's also not a workshop about R. You do not need to know R to gain from this workshop, but he will demonstrate some R tools that will hopefully get you to consider transitioning to R.

Date/Time14/06/2018 14:00-17:00
VenueCPD 2.37
LanguageEnglish

Registration Instruction

Registration is open from 25/04/2018 17:00(HKT) to 13/06/2018 18:00(HKT) on a first-come-first-served basis.

* Registration is now closed.

Contact Information

Should you have any enquiries, please feel free to contact Penny Kuk by email at pkuk@hku.hk or by phone at 39172376.