Bioequivalence and Bioavailability Forum • Rounding

Rounding [Software]

posted by Helmut – Vienna, Austria, 2013-01-04 18:35 (4122 d 06:05 ago) – Posting: # 9786
Views: 11,677

Dear Detlew!

❝ SAS 9.2: round(125.005,0.01) → 125.01

❝ (Note the definition of rounding to 2 decimals as rounding to multiples of 0.01)

There is a similar function in Excel (has to be activated in Add-ins: Analysis Toolpak):
mround(125.005,0.01) → 125.01
But – like R:
Maxima: round(125.005*100)/100 → 125.00

❝ A more drastically example, may be important also in normal life I think:

❝ round(c(0.5,1.5,2.5,3.5,4.5,5.5),0)

❝ [1] 0 2 2 4 4 6

❝ At least in Germany one would expect:

❝ [1] 1 2 3 4 5 6

Splendid.

❝ Wow! Seems rounding the CI anyhow is not such a good idea.

Yes. Not so important for the conventional acceptance range, but we have double rounding for NTIDs (AR 90.00–111.11%). Must not forget to state theta2=1.1111 in sampleN.TOST explicitly.

❝ [edit]Also the rounding seems to be implied by regulatory definitions of the acceptance range as 80.00 - 125.00 (EMA & FDA)![/edit]

Well, the width of FDA's/EMA's AR is not 45% but 125.004–79.995=45.009%…

</nitpick>

❝ But ... IMHO this must be independent from the used rounding method for 5 except the magnitude of deviation from the not rounded results since all the other results >125.0000 - 125.0049 will be also counted as BE if rounded and as not BE if not rounded.

Right. Maybe I will run a set and save individual results to a file. In the meantime I finished my balanced cross-over sim’s. n 12–60, CV 6–100%. With my grid I have 306·10⁶ sim’s each. With rounding I got 24 (7.84%) empiric alphas significantly >0.05; without 11 (3.59%). If I take power.TOST(CV=…, n=…, theta0=1.25) as the gold standard and calculate the %RSE of the simulated alphas I see a positive bias of the rounding again:

Q I median Q III rounded -0.110 +0.218 +0.574 unrounded -0.404 -0.036 +0.325

Jiří showed me another gem. Try

sprintf("%.2f", round(125.005, 2)) sprintf("%.2f", 100*round(1.25005, 4))

Edit: 2012-01-05
After reading a lot of stuff on the net I guess the only way to get “commercial rounding” (the one we learned in school; 1–4 down, 5–9 up) in R without requiring a library is by a function (THX to an anonymous poster):

cround <- function(x,n){ z <- abs(x)*10^n z <- z + 0.5 z <- trunc(z) z <- z/10^n z*sign(x) }

round(c(79.994, 79.995, 125.004, 125.005), 2)

79.99  80.00 125.00 125.00

cround(c(79.994, 79.995, 125.004, 125.005), 2)

79.99  80.00 125.00 125.01

But note:

round(c(0.79994, 0.79995, 1.25004, 1.25005), 4)

0.7999 0.8000 1.2500 1.2501

cround(c(0.79994, 0.79995, 1.25004, 1.25005), 4)

0.7999 0.8000 1.2500 1.2501

Sometimes R drives me nuts.

—
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Helmut Schütz

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Complete thread:

Rounding Helmut 2013-01-01 16:51 [Software]
- Rounding d_labes 2013-01-02 12:51
  - RoundingHelmut 2013-01-04 17:35
    - Rounding d_labes 2013-01-05 19:25
      - Rounding Helmut 2013-01-05 20:13
        
        Sim’s are sim’s are sim’s d_labes 2013-01-05 20:57
      - Another vicious circle Helmut 2013-01-06 02:21
        
        Where all these numbers came from? d_labes 2013-01-07 15:52
        
        Flaw in the GL? Helmut 2013-01-07 17:29
        
        Flaw in the GL? d_labes 2013-01-08 11:44
        
        What a mess! Helmut 2013-01-08 19:08
        
        What a mess! d_labes 2013-01-09 10:33
        
        What a mess! Helmut 2013-01-09 15:18
- Rounding ElMaestro 2013-01-02 16:12
  - Abandon rounding Helmut 2013-01-02 17:04
- Rounding yjlee168 2013-01-05 23:15
  - Rounding Helmut 2013-01-06 03:29
  - Rounding Helmut 2013-01-06 15:34
    - Rounding yjlee168 2013-01-06 23:38