tag:blogger.com,1999:blog-31819641.post5615020322528999601..comments2023-10-06T03:21:26.130-07:00Comments on trust but verify: Highly, highly unlikely?DBrowerhttp://www.blogger.com/profile/17718913310467614671noreply@blogger.comBlogger14125tag:blogger.com,1999:blog-31819641.post-7332479826438217282008-08-17T09:12:00.000-07:002008-08-17T09:12:00.000-07:00larry,That's not a bad outline of how to design te...larry,<BR/><BR/>That's not a bad outline of how to design tests.<BR/><BR/>Of course, the smaller the sample in your testing, the less appropriate it is for establishing your distribution. You'll probably not get the wings well-represented, but you might get (un)lucky and find someone with unusual characteristics.<BR/><BR/>The more important the testing, the larger the study should be to establish the distribution.<BR/><BR/>Also, this all presumes that the distribution is gaussian. This is a very common approach, but it isn't always valid. <BR/><BR/>As it all applies to this, I've never found anything to indicate that WADA ever did this stuff in more than an eyeballed way. Go to dailypelotonforums, and search for Maitre or Catlin to find the discussions there on this subject. IIRC, Maitre recommends a higher threshold, and my analysis of Catlin finds "false positives" within their presumed normal dataset.<BR/><BR/>tomThomas A. Finehttps://www.blogger.com/profile/15734341507092908270noreply@blogger.comtag:blogger.com,1999:blog-31819641.post-69409299839459585702008-08-16T23:05:00.000-07:002008-08-16T23:05:00.000-07:00Tom -First of all, how well do you understand all ...Tom -<BR/><BR/>First of all, how well do you understand all of these statistics? I don't know your background. I have a bunch of statistics questions and I need the help of a qualified statistician (not a category in my local yellow pages).<BR/><BR/>I am slowly working my way through the 2001 Catlin article in Clinical Chemistry, that's supposedly one of the pillars for the CIR testing in WADA world. It seems relatively light on chemistry and very heavy on statistics (I'm ok with that split as I know next to nothing about either subject). If I had to summarize Catlin's methodology in a nutshell, it would be:<BR/><BR/>1. Find some measurement like C13/C12 that supposedly relates to what you want to test.<BR/><BR/>2. Try out the measurement on a negative control group to establish a mean and a standard deviation.<BR/><BR/>3. Move three standard deviations away from the measured mean. This is going to be the bright line you're going to use to separate positive from negative results.<BR/><BR/>4. Find a positive control group, or a suspected positive control group, and try out the test on the group. If you get a decent percentage of the group to test positive, voila! Your test is ready for prime time.<BR/><BR/>5. Publish a paper. Accept speaking engagements. Testify against athletes (optional).<BR/><BR/>Do I understand this more or less correctly?<BR/><BR/>By the way, off topic: a while back you took me to task for "assuming" that on average 5aA, 5bA and 5bP readings for a non-doping sample should all be roughly the same value. Hey, I SAID it was an assumption. Turns out the assumption is not true. 5aA appears to have a naturally more negative delta than the other metabolites. Catlin says so in his paper. In fact, his 2001 negative control group had a mean average 5aA - 5bP of -2.1. More on this later as I absorb information.Larryhttps://www.blogger.com/profile/08976868079076669453noreply@blogger.comtag:blogger.com,1999:blog-31819641.post-3448276618057755702008-08-16T21:59:00.000-07:002008-08-16T21:59:00.000-07:00"Are you saying there was a major cycling event wi...<I>"Are you saying there was a major cycling event without much blood doping? Not likely."</I><BR/><BR/>In order for any test to be useful, it has to separate the good from the bad in some way - it has to be able to see them as two distinguishable groups. This is the perfect graph for visualizing that - you would literally see two groups of data points.<BR/><BR/>But since we don't see anything like that, there's a narrow range of possibilities. Here's some of the points on the curve:<BR/><BR/>1. delta-Hb might be a fabulous indicator of doping, but the delta value must be much higher than Floyd's numbers, and in this graph, no one doped.<BR/><BR/>2. A very small number of people doped, and delta-Hb is a poor indicator of blood doping because natural variations are similar to doping indicators.<BR/><BR/>3. Lot's of people doped, but delta-Hg is almost completely uncorrelated to doping. <BR/><BR/>tomThomas A. Finehttps://www.blogger.com/profile/15734341507092908270noreply@blogger.comtag:blogger.com,1999:blog-31819641.post-76672596455678815752008-08-16T11:53:00.000-07:002008-08-16T11:53:00.000-07:00There's a followup post, in which I counted dots a...There's a followup post, in which I counted dots and got slightly different numbers than Larry, but the gist is the same.<BR/><BR/>TBVDBrowerhttps://www.blogger.com/profile/17718913310467614671noreply@blogger.comtag:blogger.com,1999:blog-31819641.post-46432560783429814712008-08-16T11:38:00.000-07:002008-08-16T11:38:00.000-07:00M -It is always good to hear from you.OK, because ...M -<BR/><BR/>It is always good to hear from you.<BR/><BR/>OK, because you asked, I printed out a copy of figure 1 and started counting dots. Anyone else who wants to do so can do the same.<BR/><BR/>I count 154 dots, 118 below the line, 4 on the line and 32 above the line. The percentage calculation varies depending on how you count the dots on the line. If you're trying to figure out the percentage of dots above the line, I calculate 20.1%. If you're trying to figure the percentage of dots on and above the line, I calculate 23.4%. I think this is reasonably close to 25%. To be sure, even 20.1% could not fairly said to be highly highly unlikely.<BR/><BR/>You then raised the question, maybe it's not the increase in Hg per se that's highly highly unlikely, but the increase of 0.6 that's highly highly unlikely. So I printed out a copy of figure 1, and drew a line parallel to the line shown in figure 1, only 0.6 higher. I count 18 dots on or above the 0.6 line, or about 11.7%. <BR/><BR/>I don't know if it's fair to group Landis in the 11.7% group or in the 23.4% group. Grouping Landis in the 11.7% group means you're counting Landis only with those who had his "score" or higher. But even if you thought that 11.7% is the right number, I don't think that 11.7% is highly highly unlikely. If 11.7% is highly highly unlikely, then looking at the perspective of an entire year, it's even more highly highly unlikely for a day to fall in the month of August.Larryhttps://www.blogger.com/profile/08976868079076669453noreply@blogger.comtag:blogger.com,1999:blog-31819641.post-88226787630206921782008-08-16T10:28:00.000-07:002008-08-16T10:28:00.000-07:00TBV,Don't know if your 25% estimate of HB increasi...TBV,<BR/><BR/>Don't know if your 25% estimate of HB increasing in the Saugy data 7 days after is accurate or not. How was it computed?<BR/><BR/>But even if it is accurate, Ashenden wasn't speaking about just any increase, but specifically one from 15.5 to 16.1 HB.<BR/><BR/>"“Going from 15.5 to 16.1 (in hemoglobin) ...is very unusual to see an increase after a hard week of cycling... An increase like this in the midst of the Tour de France would be highly, highly unlikely."<BR/><BR/>Using those HB figures, you'd find a much smaller percentage in the Saugy data increasing to the same extent as Landis, by my very rough eyeball estimate 5 to 10%. Does this reach the "very unusual" or "highly highly unlikely" standard? Probably. 5% is the usual standard for statistical significance which might correspond to "highly highly unlikely".<BR/><BR/>But the proper way to do this is to compute a regression line estimate and the standard error of the estimate and then compare Landis's score with that standard error. <BR/><BR/>So my best guess is that the Saugy figures support Ashenden's characterization, and is not inconsistent as you are claiming.mhttps://www.blogger.com/profile/11845675234084955737noreply@blogger.comtag:blogger.com,1999:blog-31819641.post-1544972443356599422008-08-16T10:06:00.000-07:002008-08-16T10:06:00.000-07:00Tenerifed -wschart, well said! To clarify: I am n...Tenerifed -<BR/><BR/>wschart, well said! To clarify: I am not looking for proof that Landis did not blood dope. No such thing can be proven. No rider can prove he is clean. <BR/><BR/>I am saying that there is no proof that Landis blood doped. There is no proof that Landis took EPO, or took any other banned substance to produce the Hg readings from the 2006 TdF. None. <BR/><BR/>The absence of proof of doping is not, of course, proof of no doping. But there is no such thing as proof of no doping. The absence of proof of doping is the only evidence available to a clean rider to show that he is riding clean.<BR/><BR/>You have cited authority to the effect that Landis' 2006 blood readings were highly, highly unlikely. TBV has shown you proof on figure 1 that this is not so -- and the proof is from a WADA lab, not from the Landis team. As TAF points out, the Landis values fall squarely within the expected statistical distribution of values shown on figure 1. If you add a margin of error to the Landis readings (and based on what we've seen from the ACE and UCI testing, there is SOME margin of error in this testing), I would argue that the Landis readings are not unlikely at all. <BR/><BR/>TBV and I have both stated that we'd have no problem with riders shown above the figure 1 diagonal line being subject to further testing, but I'd expect a very high rate of negatives if this group actually was tested further. I've pointed out that about 5% of the riders targeted for additional testing at this year's TdF had reported AAFs, meaning that 95% of these targeted riders tested negative. Obviously, I have no way of knowing whether the riders above the figure 1 diagonal line would test positive and negative at this same rate. I'm pointing out the 5% - 95% split to show the nature and extent of the "suspicion" that is appropriate when a rider is targeted for further testing. <BR/><BR/>Again, remember that 50+ riders were targed in this year's Tour de France, because of some "suspicion" on the part of the race authorities. These "suspicious" riders included most of the brightest lights in the Tour, such as the Schleck brothers and Carlos Sastre. Even Garmin-Chipotle riders like David Millar were reportedly targeted. None of these riders tested positive for blood doping or EPO. There is no lingering "suspicion" of these riders, nor should there be. Similarly, Landis was tested 8 times during the 2006 TdF, and never tested positive for blood doping or EPO. On the topic of blood doping and EPO, Landis also merits no lingering suspicion.<BR/><BR/>The bigger point being made by TBV is that you cannot make too big a deal about the Landis blood numbers. There's little if anything that you can conclude from these numbers.Larryhttps://www.blogger.com/profile/08976868079076669453noreply@blogger.comtag:blogger.com,1999:blog-31819641.post-81407209285847348982008-08-16T09:50:00.000-07:002008-08-16T09:50:00.000-07:00All this is not really an attempt to show that Lan...All this is not really an attempt to show that Landis didn't blood dope, but rather an attempt to show that the 48.2 figure often referred to as evidence of doping is far from conclusive evidence of doping. It might raise some suspicions, but that is all.wscharthttps://www.blogger.com/profile/14580006249706915137noreply@blogger.comtag:blogger.com,1999:blog-31819641.post-11797669478131953252008-08-16T08:37:00.000-07:002008-08-16T08:37:00.000-07:00Larry - You are looking for proof Landis did not b...Larry - <BR/>You are looking for proof Landis did not blood dope. You found evidence in Figure 1. That evidence means nothing if cyclists in Figure 1. were blood doping. You said yourself doping is not unusual in cycling. Increasing Hb caused by doping is not unusual. This real world example does not help your point.<BR/><BR/>Thomas -<BR/>Are you saying there was a major cycling event without much blood doping? Not likely.Tenerifedhttps://www.blogger.com/profile/09691795403823730559noreply@blogger.comtag:blogger.com,1999:blog-31819641.post-62443217526517356232008-08-16T06:55:00.000-07:002008-08-16T06:55:00.000-07:00Good morning everyone! Larry, TAF, TBV you guys ...Good morning everyone!<BR/> Larry, TAF, TBV you guys are on a fantastic roll ! I am dazzled.<BR/><BR/> Hope SYI and Bill are getting some rest and reloading their arsenals :-).<BR/><BR/> I saw Ali's post the other day.<BR/>Ali - come on in the waters fine!<BR/><BR/> Did anyone notice that Phelps had submitted to special intense testing to prove he is clean ? And he is collecting all that gold with only half of the niki suit! Maybe he has an invisible underwater Harley :-)<BR/><BR/> Going for a ride :-)<BR/><BR/>Regards, <BR/>RussRusshttps://www.blogger.com/profile/00725508645675310008noreply@blogger.comtag:blogger.com,1999:blog-31819641.post-82595978482366993162008-08-16T00:21:00.000-07:002008-08-16T00:21:00.000-07:00tenerifed, don't be ridiculous.That's a beautiful ...tenerifed, don't be ridiculous.<BR/><BR/>That's a beautiful plot. It's a nice smooth distribution, with a denser core, and gradually falling off evenly in all directions.<BR/><BR/>Doping would be indicated (ideally) by an isolated clump of values, or at least by a lopsided graph.<BR/><BR/>tomThomas A. Finehttps://www.blogger.com/profile/15734341507092908270noreply@blogger.comtag:blogger.com,1999:blog-31819641.post-74189322567437720972008-08-15T23:47:00.000-07:002008-08-15T23:47:00.000-07:00t-fed, come on. You cited an authority that said ...t-fed, come on. You cited an authority that said that a rise in Hg levels would be highly, highly unlikely. Figure 1 is relevant, as it shows that a rise in Hg levels happens about 25% of the time. That's not unlikely.<BR/><BR/>Sure, we can guess that some number of the cyclists represented in figure 1 might have been doping. What is your point? That you don't think we should look at the results from the real world? You cannot study the results of any race going back 25 years or more where we'd assume we were dealing with a 100% clean peloton. In fact, we can say with some confidence that a 100% clean peloton is highly, highly unlikely.Larryhttps://www.blogger.com/profile/08976868079076669453noreply@blogger.comtag:blogger.com,1999:blog-31819641.post-85747102173319223472008-08-15T22:39:00.000-07:002008-08-15T22:39:00.000-07:00Some of the cyclists in Figure 1. were doping. Fig...Some of the cyclists in Figure 1. were doping. Figure 1. is irrelevant.Tenerifedhttps://www.blogger.com/profile/09691795403823730559noreply@blogger.comtag:blogger.com,1999:blog-31819641.post-47487126866145794702008-08-15T21:38:00.000-07:002008-08-15T21:38:00.000-07:00Uggh. I really had hoped that I had long ago driv...Uggh. I really had hoped that I had long ago driven a stake through the heart of the ridiculous testosterone-through-blood-doping theory. And here I find my good friend TBV mentioning it, and then doing a poor job of beating the dead horse to make sure it doesn't jump up again and start demanding brains.<BR/><BR/>Night of the Living Horribly Stupid Theory.<BR/><BR/>So anyway, the two other really good reasons why this dog won't hunt, and won't even get out of bed, because it is in fact a dead dog, with no handy zombie chemicals nearby are:<BR/><BR/>1. The half-life of testosterone in the blood is very short, less than an hour, so unless he took testosterone and then immediatly drew a blood sample, there would no testosterone in the blood to reintroduce.<BR/><BR/>2. Blood doping is not a total blood replacement. You're adding maybe 10% new blood. So whatever testosterone there was in your testosterone originally (which is probably none, see above), and which was not eliminated in processing (see TBV's description) would only have a 1/10th measureable effect.<BR/><BR/>This is the most important argument. Normally, doping with T mixes natural and synthetic testosterone, and you get a carbon-13 measurement that's somewhere in between. If someone had a fairly high carbon-13 baseline of -20, then compared to the roughly -30 value for synthetic, doubling your testosterone through doping would produce a result of -25.<BR/><BR/>So, IF Floyd injected testosterone and immediately drew blood, and by some miracle the testosterone got passed the blood processing, then reintroducing that blood for a 10% increase in blood volume could conceivable alter the carbon-13 measurement by around 0.5.<BR/><BR/>tomThomas A. Finehttps://www.blogger.com/profile/15734341507092908270noreply@blogger.com