Subject: Help Needed: Managing Missing Values in Jamovi (Mean, Median, Multiple Imputation)

[arshishad]

Hello Jamovi Community,

I’m currently working on a dataset in Jamovi and facing challenges with handling missing values. I’ve read that there are various methods available like replacing missing values with mean or median, and also more advanced approaches like multiple imputation. However, I’m struggling to figure out how to actually perform these operations within Jamovi.

Could someone kindly guide me through:

The steps to replace missing values with mean or median in Jamovi?

Whether multiple imputation is supported natively or requires an add-on module (like 'mice' or 'jmv')?

Any suggestions on best practices or considerations while dealing with missing data in Jamovi?

Any help, screenshots, or links to tutorials/documentation would be greatly appreciated.

Thanks in advance for your support!

[jonathon]

take a look at example 3 in this blog post:

https://blog.jamovi.org/2018/10/23/tran ... ables.html

jonathon

[MAgojam]

Hey @arsishad,

if you took a look at the link that Jth suggested, you will have no problem understanding the screenshot that I attach, because in addition to the VMEAN($source) for the mean, you also have the possibility of using VMED($source) for the Median, VMAD($source) for the Median Absolute Deviation the VMADR($source) for the Median Absolute Deviation Robust.

They are not present in the jmv Basic Analysis module, but in jamovi because they are python code.

Probably in the future more complex functions could be available for iterative processes such as the "Fully Conditional Specification" (FCS) or imputation for chain equations which is the algorithm that MICE uses.

VMEAN_missing.png (191.79 KiB) Viewed 30495 times

Cheers,
Maurizio

[yurismol]

There is a missForest library, but I only plan to include it in the module. Maybe this can be included manually with R code?

[arshishad]

Thank you for quick responses.