## bootf2bca v1.2 [Software]

Dear all,

we discussed the code at BioBridges…

The problem with reproducibility can easily be solved.

In

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

The current version 1.2 is a

The cut-off preferred by the EMA is implemented:

Don’t get confused by

» 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

I prefer Freedman–Diaconis* and show additionally the median and 90% CI.

we discussed the code at BioBridges…

The problem with reproducibility can easily be solved.

In

`F2_boot.R`

after line 270 `#main algorithm`

add *e.g.*,`set.seed(123456)`

.» 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:

Don’t get confused by

**Q>=85%**. Actually it is the correct**>85%**. Still missing: one value >85% for the test (FDA) and one value >85% for the reference (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 ƒ_{2}values from the file and generate your own histogram (density instead of counts). I don’t like the one of`plotly`

. Way too many bins for my taste (here an example with 5,000 bootstraps).I prefer Freedman–Diaconis* and show additionally the median and 90% CI.

- Even if you specify
`hist(..., breaks="Freedman–Diaconis")`

this is not what you might expect from the Freedman–Diaconis rule \(width=2\frac{IQR(x)}{\sqrt[3]{n}}\) and \(bins=(max(x)-min(x))/width\).

The man-page of`hist`

states:

[…] the number is a suggestion only; as the breakpoints will be set to`pretty`

values.

In my example I got 34 bins instead of the desired 47 (IQR=2.9026, n=5,000, min=55.76, max=71.73). Workaround (`x`

are the bootstrapped ƒ_{2}-values):

`width <- 2*IQR(x)/length(x)^(1/3)`

bins <- as.integer(diff(range(x)) / width)

hist(x, breaks = seq(min(x), max(x), length.out = bins), freq = FALSE)

—

Helmut Schütz

The quality of responses received is directly proportional to the quality of the question asked. 🚮

Science Quotes

*Dif-tor heh smusma*🖖Helmut Schütz

The quality of responses received is directly proportional to the quality of the question asked. 🚮

Science Quotes

### Complete thread:

- Validation of PhEq_bootstrap Helmut 2018-07-12 17:47 [Software]
- Validation of PhEq_bootstrap ElMaestro 2018-07-12 22:21
- Validation of PhEq_bootstrap Helmut 2018-07-13 01:29
- Validation of PhEq_bootstrap ElMaestro 2018-07-13 10:14
- Validation of PhEq_bootstrap Helmut 2018-07-13 12:54
- Validation of PhEq_bootstrap ElMaestro 2018-07-13 14:28

- Validation of PhEq_bootstrap Helmut 2018-07-13 12:54

- Validation of PhEq_bootstrap ElMaestro 2018-07-13 10:14

- Validation of PhEq_bootstrap Helmut 2018-07-13 01:29
- Validation of PhEq_bootstrap Shuanghe 2018-07-17 15:54
- PhEq_bootstrap in R d_labes 2018-08-15 09:45
- bootf2bca v1.2Helmut 2019-10-05 00:59

- Validation of PhEq_bootstrap ElMaestro 2018-07-12 22:21