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ADVS template for growth parameters #32
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From the above we understood to create in total 5 metadata sets from the 15 datasets as following:
Could you please confirm our understanding ? Thank you. |
@Fanny-Gautier yes, that's right, and some additional points:
This should be done in a file named |
is 2 years <731 days or <= 729 ? In the ADVS specs we talk about <731 days... |
@Fanny-Gautier given to account for leap year we usually assume a year is 365.25 days so that means we should include up to 730 days from WHO and 731 days onwards from CDC. sorry for confusing above with the mention of 729 |
ADVS template: could you please guide us for the merge of ADSL variables (TRTSDT) since these are not the same patients as in dm_peds ? I am not sure to understand how to proceed with step 3 (Computing AAGECUR) and merge ADSL variables from step 1b. |
@Fanny-Gautier i spotted same today (see discussion at pharmaverse/pharmaversesdtm#88). for now just use the |
I wouldn't impute partial birth dates for the template - let's keep this example simple. I saw the test data has one such case but think we could update this later to make all dates complete. I'd expect most trials have complete birth dates and I wouldn't want to estimate what the appropriate imputation rule might be if they didn't. For the issue with the code, feel free to email me the full code you're running and I could try and figure out on my side. I don't see anything obvious from your screenshot. |
… Derived z-score and percentile parameters for BMI, WEIGHT and Head circumference.
…GHT variable. and modified the function call derive_params_growth_age to keep the derived parameters and corresponding input records only.
Delete line of code mutate(AVALC = VSSTRESC) as per Nancy's comment |
Co-authored-by: Ross Farrugia <[email protected]>
…d HEIGHT_LENGTHU in both who_wt_for_lgth and who_wt_for_ht metadata
See the outline document in MS Teams area. Steps 5 and 6 rely on the new functions being available so placeholders will be needed for now.
The main part will be Step 4 for preparing the metadata into a consistent structure covering the below points:
PROPOSAL FOR BY AGE: In this step for each of BMI/HEIGHT/WEIGHT, we would combine WHO <2yrs and CDC >=2 data into one single consistently structured meta dataset (with
SEX
as a variable - withM
andF
values,AGE
in days via a conversion factor). Clearly comment to make clear here our default reference source, in our case WHO <2 yrs and CDC >=2, and the fact that any user could replace this with their own chosen metadata. We can explain this then more in the vignette.PROPOSAL FOR THE WHO-ONLY DATA: In this step for each of HEAD CIRCUMFERENCE and WEIGHT (BY LENGTH/HEIGHT), we would combine the boys and girls data into one single consistently structured meta dataset (with
SEX
as a variable - withM
andF
values). For WEIGHT (BY LENGTH/HEIGHT) additionally then combine the LENGTH and HEIGHT data into one single dataset with additional variableMEASURE
to denote LENGTH or HEIGHT andHEIGHT_LENGTH
variable showing the length/height values.The naming of these meta datasets should still clearly convey which parameter they each relate to, so then no need to add PARAMCD here as a variable in these datasets.
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