Skip to content

Conversation

@zenourn
Copy link
Collaborator

@zenourn zenourn commented Jan 13, 2022

…s in neuropsych export. Also include diagnostic variables in concise output.

…s in neuropsych export. Also include diagnostic variables in concise output.
@zenourn zenourn requested a review from m-macaskill January 13, 2022 21:47
Copy link
Contributor

@m-macaskill m-macaskill left a comment

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Oops, it was my understanding that global z was (or should be) the mean of the domain mean z-scores, rather than a grand mean of all constituent scores (which will give more weight to a domain with more tests)? What is the actual calculation, and does this cause issues for our previous publications?

@kylahorne

@kylahorne
Copy link
Collaborator

kylahorne commented Jan 14, 2022 via email

@zenourn
Copy link
Collaborator Author

zenourn commented Jan 14, 2022

This came up with Kyla's paper where we described it correctly on pg 393: "... global cognitive score (expressed as an aggregate z score derived from averaging performance from measures conducted across the five cognitive domains)..." We decided to have global_z_historical (which Michael renames to "global_z_no_language" in chchpd) which is the mean of domain means without language, and global_z as the grand mean of all z scores. We discussed this in detail at the time, but effectively taking the mean of all the scores has better properties than when taking it by domain and including language which we now want to do, primarily due to many older sessions only having a single language test thus that having too much weight when taking the mean by "domain". John has also changed which domain several tests are in since the start of the study (was rather fluent with them during the optimal tests paper process) and taking this approach means their weighting is invariant whatever domain they are put in. I have also done a thorough review of the historical z score code calculation, and did find a small error in relation to what was happening when there are two non-independent tests (i.e., the CVLT short and long). This is now fixed and I really need to get unit tests in place as there is so much complexity in the pipeline where things can go wrong.

@zenourn
Copy link
Collaborator Author

zenourn commented Jan 18, 2022

I've done a quick literature review of how other people calculate global z. There is a real mixture, however the mean of domain means seems to be the most common, followed my the grand mean, and then there are other cases where calculate means by domain but then standardise these before calculating the global z. If we are going to make a change, now is a good time to do it while documenting and because everyone needs to update their data anyway (due to the duplicate data fixes, changes to NA3 imputations when entire test is missing, and fixes to z-score calculations). Do we want to want to make the default global_z the mean of domain means excluding language? Then have a new global_z_grand_mean and global_z_with_language?

@m-macaskill
Copy link
Contributor

Do we want to want to make the default global_z the mean of domain means excluding language? Then have a new global_z_grand_mean and global_z_with_language?

I think that would be the ideal outcome - everyone gets to choose the version they want, but the default global_z matches what most of us think it was/should have been.

@kylahorne
Copy link
Collaborator

kylahorne commented Jan 19, 2022 via email

Hopefully getting close to final definitions and is what I'll change redcap export code to return. Not ready for merging - needs to be linked to the new Google Sheets in the new drive once they exist.
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment

Labels

None yet

Projects

None yet

Development

Successfully merging this pull request may close these issues.

4 participants