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nutriverse / ipctools

Utilities to Support Integrated Food Security Phase Classification (IPC) Data Processing and Visualisation
https://nutriverse.io/ipctools/
GNU General Public License v3.0
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add function/s to classify p-values for sex ratio and age ratio tests #3

Closed ernestguevarra closed 8 months ago

ernestguevarra commented 10 months ago

based on conversations with @tomaszaba, IPC uses the following criteria to classify p-value results of sex ratio and age ratio tests:

image

Functions that perform these classifications would be helpful. Note that for digit preference, such a classification already exists and is produced as part of the output of the digitPreference() function.

It might be logical to use the same approach for sex ratio and age ratio.

ernestguevarra commented 10 months ago

@tomaszaba I added you here so that you can aim to contribute to this package with a classifier code similar to what you have in your MUAC quality checks script.

Note that package development and maintenance is a little bit different than just writing scripts. It is all about function writing but at the same time writing them in such a way that the function will be usable not just by you or your project but by a broad user base. So the approach is more universal type of coding with some appreciation of user experience.

This is not urgent. And I think we need to have a few more meetings where we just train in package creation. The best reference for this is - https://r-pkgs.org/.

Again, this should not be the priority. We should do this when you are not busy from work and have some free time.

tomaszaba commented 8 months ago

@ernestguevarra thank you. Happy to contribute to this package. On package writing, I will follow your guidance on when you can start training me on this subject. I have bookmarked this resource you shared, but haven't started reading it yet as I was reading and practicing R for Data Science (2ed).

Also, I think I have seen that you have already added to this package functions classify_quality() and that we worked on the IPC muac quality checks project.

ernestguevarra commented 8 months ago

@ernestguevarra thank you. Happy to contribute to this package. On package writing, I will follow your guidance on when you can start training me on this subject. I have bookmarked this resource you shared, but haven't started reading it yet as I was reading and practicing R for Data Science (2ed).

Also, I think I have seen that you have already added to this package functions classify_quality() and that we worked on the IPC muac quality checks project.

See my comment here - https://github.com/nutriverse/ipctools/issues/4. I think we should create a package specific for your use with IPC practices and principles. I know we are just working on MUAC but I am sure you have other things that you are doing routinely that would be good to put in an R package so you can re-use all the time.