Code for setting up DiD analysis for wider project
mrc-cso-sphsu / uc-did-analysis Goto Github PK
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License: MIT License
There should be documentation discussing naming conventions and the package structure itself, some common features are listed right below:
Make a new variable with binary married/cp/ch vs not outcome.
Use of QUAL_[1-35]
excludes non-UK qualifications. Change to use HIQUL11D/HIQUL15D
instead
I tried to run the project on the workstation using the data you sent me. It fails with this message:
Error in `group_by()`:
! Must group by variables found in `.data`.
✖ Column `benefit` is not found.
Backtrace:
▆
1. ├─ggplot2::ggplot(...)
2. ├─dplyr::arrange(...)
3. ├─dplyr::filter(...)
4. ├─dplyr::mutate(...)
5. ├─dplyr::summarise(...)
6. ├─dplyr::group_by(...)
7. └─dplyr:::group_by.data.frame(...)
8. └─dplyr::group_by_prepare(.data, ..., .add = .add, caller_env = caller_env())
9. └─rlang::abort(bullets, call = error_call)
Execution halted
What do you think went wrong?
Since we run everything in parallel im might be a good idea to employ installed GPUs.
R provides some opportunities for that, however, I'm not sure your current code is 100% compatible with that.
That should theoretically make your calculations blazingly fast. Not sure about the accuracy though, single precision floating-point numbers can be pretty nasty.
Hi @vkhodygo - have updated the code in the optimise_predictions.R
file to run a full set of optimising predictions. Will be a little longer than trial versions. Could you run then send the .rds
files from the output
folder (via email or onedrive)?
Most things fixed and should run smoothly, but let me know if not.
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