Arbitrary (and unjustified) cut-off of r² [RSABE / ABEL]
Dear Detlew & AB!
Yes! Explained variance (sloppy: information) in regression (strongly!) depends on the sample size. See here and a rather lengthy thread of 2002 at David Bourne’s PKPD-list.
Critical values of \(\small{r}\) according to Odeh (1982)1 (and modified for \(\small{r^2}\)); one sided, 5%:$$\small{\begin{array}{rcc}
n & r & r^2\\\hline
3 & 0.9877 & 0.9755\\
4 & 0.9000 & 0.8100\\
5 & 0.805\phantom{0} & 0.6486\\
6 & 0.729\phantom{0} & 0.5319\\
7 & 0.669\phantom{0} & 0.4481\\
8 & 0.621\phantom{0} & 0.3863\\
9 & 0.582\phantom{0} & 0.3390\\
10 & 0.549\phantom{0} & 0.3018\\
11 & 0.521\phantom{0} & 0.2719\\
12 & 0.497\phantom{0} & 0.2473\\
13 & 0.476\phantom{0} & 0.2267\\
14 & 0.457\phantom{0} & 0.2093\\
15 & 0.441\phantom{0} & 0.1944\\\hline
\end{array}}$$ In other words, an \(\small{r^2}\) of 0.6486 from five data points denotes the same ‘quality of fit’ than an \(\small{r^2}\) of 0.9755 from three. Searching the forum I get the impression that you (AB) are not alone with a cut-off of 0.80. Justification: nil. Maybe there is some copypasting going on? If you really want to use a cut-off (which I don’t recommend and is not required in any GL) take the number of data points into account. I strongly suggest to revise your SOP.
BTW, visual inspection of fits is mandatory (see there with references). Don’t trust in numbers alone. A classical example is Anscombe’s quartet.2
❝ Not to calculate the AUC(0-inf) values if the fit of the terminal part of the concentration-time curves had an r2 value less than 80% is at least statistically not very sound, not to say nonsense IMHO .
Yes! Explained variance (sloppy: information) in regression (strongly!) depends on the sample size. See here and a rather lengthy thread of 2002 at David Bourne’s PKPD-list.
Critical values of \(\small{r}\) according to Odeh (1982)1 (and modified for \(\small{r^2}\)); one sided, 5%:$$\small{\begin{array}{rcc}
n & r & r^2\\\hline
3 & 0.9877 & 0.9755\\
4 & 0.9000 & 0.8100\\
5 & 0.805\phantom{0} & 0.6486\\
6 & 0.729\phantom{0} & 0.5319\\
7 & 0.669\phantom{0} & 0.4481\\
8 & 0.621\phantom{0} & 0.3863\\
9 & 0.582\phantom{0} & 0.3390\\
10 & 0.549\phantom{0} & 0.3018\\
11 & 0.521\phantom{0} & 0.2719\\
12 & 0.497\phantom{0} & 0.2473\\
13 & 0.476\phantom{0} & 0.2267\\
14 & 0.457\phantom{0} & 0.2093\\
15 & 0.441\phantom{0} & 0.1944\\\hline
\end{array}}$$ In other words, an \(\small{r^2}\) of 0.6486 from five data points denotes the same ‘quality of fit’ than an \(\small{r^2}\) of 0.9755 from three. Searching the forum I get the impression that you (AB) are not alone with a cut-off of 0.80. Justification: nil. Maybe there is some copypasting going on? If you really want to use a cut-off (which I don’t recommend and is not required in any GL) take the number of data points into account. I strongly suggest to revise your SOP.
BTW, visual inspection of fits is mandatory (see there with references). Don’t trust in numbers alone. A classical example is Anscombe’s quartet.2
- Odeh RE. Critical values of the sample product-moment correlation coefficient in the bivariate distribution. Commun Statist–Simula Computa. 1982; 11(1): 1–26. doi:10.1080/03610918208812243.
- Anscombe FJ. Graphs in statistical analysis. Am Stat. 1973; 27: 17–21. doi:10.2307/2682899.
—
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
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:
- SAS error in 3 way ref replicate study AB 2012-05-04 15:13 [RSABE / ABEL]
- SAS error in 3 way ref replicate study jag009 2012-05-04 15:36
- SAS error in 3 way ref replicate study AB 2012-05-05 06:45
- FDA's ABE code and partial replicate design d_labes 2012-05-06 10:10
- Arbitrary (and unjustified) cut-off of r²Helmut 2012-05-06 13:29
- Anscombe quartet d_labes 2012-05-07 08:48
- Anscombe quartet in R Helmut 2012-05-07 11:15
- Anscombe quartet in R AB 2012-05-07 12:07
- Anscombe quartet in R Helmut 2012-05-07 11:15
- Arbitrary (and unjustified) cut-off of r² FI 2012-10-08 10:39
- Predominant half life; exclusions Helmut 2012-10-08 13:45
- Excluding time points for lambdaZ d_labes 2012-10-09 09:33
- Analytical variability Helmut 2012-10-09 14:09
- Answer machine d_labes 2012-10-09 15:15
- Well done! Helmut 2012-10-09 19:43
- Answer machine d_labes 2012-10-09 15:15
- Analytical variability Helmut 2012-10-09 14:09
- Excluding time points for lambdaZ d_labes 2012-10-09 09:33
- Predominant half life; exclusions Helmut 2012-10-08 13:45
- Anscombe quartet d_labes 2012-05-07 08:48
- Arbitrary (and unjustified) cut-off of r²Helmut 2012-05-06 13:29
- SAS error in 3 way ref replicate study jag009 2012-05-04 15:36