Spaghetti & other pasta [NCA / SHAM]
Dear Yung-jin!
Hhm.
No, it isn’t.
There is no interpolation done at all. Have a look at my example in the previous post. I gave the interpolation/imputation formulas only as a hint what might happen if we need an intermediate data point. If we want to calculate the area in the interval [t2, t2] no interpolation, smoothing, whatsoever is done. Both methods are straightforward:
Right.
Xactly. See also Nathan’s PK/PD Blog.
❝ Now I think that I have fully understood the differences between the linear and the lin-up/log-down method for AUC calculations.
Hhm.
❝ Actually, lin-up/log-down method is still a kind of data smoothing approach.
No, it isn’t.
❝ The key point is that involved calculation step still uses the raw data to calculate the interpolated data.
There is no interpolation done at all. Have a look at my example in the previous post. I gave the interpolation/imputation formulas only as a hint what might happen if we need an intermediate data point. If we want to calculate the area in the interval [t2, t2] no interpolation, smoothing, whatsoever is done. Both methods are straightforward:
linear: AUCt1→t2=0.5(t2–t1)(C2+C1)
linlog: AUCt1→t2=(t2–t1)(C2–C1)/log(C2/C1)
❝ As we can see, the errors between linear and lin-up/log-down become significantly apparent, especially when sampling time between two data points is getting greater.
Right.
❝ Therefore, when there is missing data occurring, the lin-up/log-down method shows more accurate than the linear.
Xactly. See also Nathan’s PK/PD Blog.
—
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Helmut Schütz
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Science Quotes
Dif-tor heh smusma 🖖🏼 Довге життя Україна!
![[image]](https://static.bebac.at/pics/Blue_and_yellow_ribbon_UA.png)
Helmut Schütz
![[image]](https://static.bebac.at/img/CC by.png)
The quality of responses received is directly proportional to the quality of the question asked. 🚮
Science Quotes
Complete thread:
- handling of missing data gracehung 2013-05-20 07:35
- Lin-up/log-down trapezoidal avoids most trouble Helmut 2013-05-20 14:22
- Lin-up/log-down trapezoidal avoids most trouble yjlee168 2013-05-22 08:25
- Multiple peaks: fallback to linear trapezoidal Helmut 2013-05-22 20:25
- Multiple peaks: fallback to linear trapezoidal yjlee168 2013-05-22 21:57
- No interpolation Helmut 2013-05-22 23:25
- No interpolation yjlee168 2013-05-23 11:43
- Spaghetti & other pasta Helmut 2013-05-23 15:15
- Spaghetti & other pasta yjlee168 2013-05-23 20:47
- Spaghetti & other pasta Helmut 2013-05-23 21:29
- Spaghetti & other pasta yjlee168 2013-05-23 22:46
- Spaghetti & other pastaHelmut 2013-05-24 01:24
- Spaghetti & other pasta yjlee168 2013-05-24 09:17
- Spaghetti & other pastaHelmut 2013-05-24 01:24
- Spaghetti & other pasta yjlee168 2013-05-23 22:46
- Spaghetti & other pasta Helmut 2013-05-23 21:29
- Spaghetti & other pasta yjlee168 2013-05-23 20:47
- Spaghetti & other pasta Helmut 2013-05-23 15:15
- No interpolation Ken Peh 2013-05-30 19:55
- Different algos! Helmut 2013-05-30 22:38
- Different algos! Ken Peh 2013-06-03 17:52
- Calculate what? Helmut 2013-06-03 18:11
- Different algos! Ken Peh 2013-06-03 17:52
- Different algos! Helmut 2013-05-30 22:38
- No interpolation yjlee168 2013-05-23 11:43
- No interpolation Helmut 2013-05-22 23:25
- Multiple peaks: fallback to linear trapezoidal yjlee168 2013-05-22 21:57
- Lin-up/log-down trapezoidal example Helmut 2013-05-25 15:09
- Lin-up/log-down trapezoidal example yjlee168 2013-05-25 19:45
- Multiple peaks: fallback to linear trapezoidal Helmut 2013-05-22 20:25
- Lin-up/log-down trapezoidal avoids most trouble yjlee168 2013-05-22 08:25
- handling of missing data Ohlbe 2013-05-20 21:45
- Sorry Helmut 2013-05-21 13:53
- Sorry gracehung 2013-05-23 01:06
- Uncertain time point Helmut 2013-05-23 01:35
- Sorry gracehung 2013-05-23 01:06
- Sorry Helmut 2013-05-21 13:53
- Lin-up/log-down trapezoidal avoids most trouble Helmut 2013-05-20 14:22