Further to the plot suggested below, the plot plot(log(A),log(B/A),pch="+",col="blue")
reveals an interesting structure to the data. Distinct curved sequences are clearly visible. While their curved form is a consequence of the fact that, for large A, A/B is close to 1 and so they tend to approach 1 "asymptotically" (hence the curving over towards flatness), what is really interesting is the appearance of distinct curves, as if there were at least 7 (or at least 8) distinct subsets to the data, each subset following a different curve. Perhaps these are related to observed variables? Ted. On 20-Sep-11 18:15:50, Ted Harding wrote: > As can be seen by plotting as follows: > > plot(A,B,pch="+",col="blue") ## The raw data > > plot(A,B-A,pch="+",col="blue") ## The differences versus A > lines(c(0,0.7),c(0,0)) > > Ted. > > On 20-Sep-11 17:54:15, Timothy Bates wrote: >> Yes, in over 3/4s of the data points A is > B which suggests the A >> measure is reading higher than the B measuring system. >> >> length(A[A>B])/length(A) >> >> >> On 20 Sep 2011, at 6:46 PM, Pedro Mardones wrote: >> >>> Dear all; >>> >>> A very basic question. I have the following data: >>> >>> ********************************************************************** >>> * >>> ************* >>> >>> A <- 1/1000*c(347,328,129,122,18,57,105,188,57,257,53,108,336,163, >>> 62,112,334,249,45,244,211,175,174,26,375,346,153,32, >>> 89,32,358,202,123,131,88,36,30,67,96,135,219,122, >>> 89,117,86,169,179,54,48,40,54,568,664,277,91,290, >>> 116,80,107,401,225,517,90,133,36,50,174,103,192,150, >>> 225,29,80,199,55,258,97,109,137,90,236,109,204,160, >>> 95,54,50,78,98,141,508,144,434,100,37,22,304,175, >>> 72,71,111,60,212,73,50,92,70,148,28,63,46,85, >>> 111,67,234,65,92,59,118,202,21,17,95,86,296,45, >>> 139,32,21,70,185,172,151,129,42,14,13,75,303,119, >>> 128,106,224,241,112,395,78,89,247,122,212,61,165,30, >>> 65,261,415,159,316,182,141,184,124,223,39,141,103,149, >>> 104,71,259,86,85,214,96,246,306,11,129) >>> >>> B <- 1/1000*c(351,313,130,119,17,50,105,181,58,255,51,98,335,162, >>> 60,108,325,240,44,242,208,168,170,27,356,341,150,31, >>> 85,29,363,185,124,131,85,35,27,63,92,147,217,117, >>> 87,119,81,161,178,53,45,38,50,581,661,254,87,281, >>> 110,76,100,401,220,507,94,123,36,47,154,99,184,146, >>> 232,26,77,193,53,264,94,110,128,87,231,110,195,156, >>> 95,51,50,75,93,134,519,139,435,96,37,21,293,169, >>> 70,80,104,64,210,70,48,88,67,140,26,52,45,90, >>> 106,63,219,62,91,56,113,187,18,14,95,86,284,39, >>> 132,31,22,69,181,167,150,117,42,14,11,73,303,109, >>> 129,106,227,249,111,409,71,88,256,120,200,60,159,27, >>> 63,268,389,150,311,175,136,171,116,220,30,145,95,148, >>> 102,70,251,88,83,199,94,245,305,9,129) >>> >>> ********************************************************************** >>> * >>> ************* >>> >>> plot(A,B) >>> abline(0,1) >>> >>> At a glance, the data look very similar. Data A and B are two >>> measurements of the same variable but using different devices (on a >>> same set of subjects). Thus, I thought that a paired t-test could be >>> appropriate to check if the diff between measurement devices = 0. >>> >>> t.test(A-B) >>> >>> ********************************************************************** >>> * >>> ************* >>> >>> One Sample t-test >>> >>> data: A - B >>> t = 7.6276, df = 178, p-value = 1.387e-12 >>> alternative hypothesis: true mean is not equal to 0 >>> 95 percent confidence interval: >>> 0.002451622 0.004162903 >>> sample estimates: >>> mean of x >>> 0.003307263 >>> >>> ********************************************************************** >>> * >>> ************* >>> The mean diff is 0.0033 but the p-value indicates a strong evidence >>> to >>> reject H0. >>> >>> I was expecting to find no differences so I'm wondering whether the >>> t-test is the appropriate test to use. I'll appreciate any comments >>> or >>> suggestions. > > -------------------------------------------------------------------- > E-Mail: (Ted Harding) <ted.hard...@wlandres.net> > Fax-to-email: +44 (0)870 094 0861 > Date: 20-Sep-11 Time: 19:15:47 > ------------------------------ XFMail ------------------------------ > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. -------------------------------------------------------------------- E-Mail: (Ted Harding) <ted.hard...@wlandres.net> Fax-to-email: +44 (0)870 094 0861 Date: 20-Sep-11 Time: 23:26:53 ------------------------------ XFMail ------------------------------ ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
