bootf2BCA v1.1 [Software]

posted by Helmut Homepage – Vienna, Austria, 2019-10-05 02:59 (1636 d 08:22 ago) – Posting: # 20665
Views: 11,613

Dear all,

we discussed the code at BioBridges…

The problem with reproducibility can easily be solved.
In the script F2_boot.R after line 270 #main algorithm add a new line

set.seed(X)

where X is an integer (specified in the protocol and report). Use

c(-1L, +1L) * .Machine$integer.max

to check the possible range. On my machine it gives

[1] -2147483647  2147483647

However, I suggest a simple one (42?).

❝ Be warned: The source code is hard to read, nearly no comments at all.


The current version 1.2 is a little bit better. Still heavy stuff.

The cut-off preferred by the EMA is implemented:

[image]

Don’t get confused by Q>=85%. That’s typo. Actually it is the correct >85%.
Still missing: One value >85% for the test (FDA) or one value >85% for the comparator (WHO).

❝ Be further warned: If you rise the number of bootstrap samples (default is 1000, too low IMHO) the result file will contain a huge number of entries, each bootstrap sample is recorded! The same mess as in the 'Object Pascal' implementation. But could of course also changed with a little knowledge of R.


Hint: In F2_boot.R comment out the loop in lines 317–329. Then the report-file shrinks from a couple of megabytes to some kilobytes. I would keep the rest for documentation. Useful to read the bootstrapped ƒ2 values from the file and generate your own histogram (density instead of counts). I don’t like the one of [image] plotly. Way too many bins for my taste (here an example with 5,000 bootstraps). \(\small{\textrm{ceiling}(\sqrt n)}\) gives 71 bins and smells of Excel.

[image]


I prefer the Freed­man–Dia­conis rule* and show additionally the median and 90% CI (green line if the lower CL ≥50).

[image]




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