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No the proper application of your metaphor would be for the elasticity to cause the rubber band to snap back into shape, not measurement error.

 

At the very least, get the right details on what he said.

Is nap time over at the free clinic?

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It's posts like the above which utterly remove the possibility of you having credibility. If you're going to throw around insults about free clinics, at least make sure your facts are straight first.

 

Wraith wrote that regression toward the mean is caused by a two part process. First, measurement error on the first test causes a distribution to appear to be more spread out than it really is. He compared this to the stretching of a rubber band. The second part of this process is when you re-measure those with the most extreme scores. On average, those scores will drift a little closer to the mean the second time around. This second part of the process is like the rubber band snapping back into its normal shape.

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It's posts like the above which utterly remove the possibility of you having credibility. If you're going to throw around insults about free clinics, at least make sure your facts are straight first.

 

Wraith wrote that regression toward the mean is caused by a two part process. First, measurement error on the first test causes a distribution to appear to be more spread out than it really is. He compared this to the stretching of a rubber band. The second part of this process is when you re-measure those with the most extreme scores. On average, those scores will drift a little closer to the mean the second time around. This second part of the process is like the rubber band snapping back into its normal shape.

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That's not what he said, and that's not true anyway. As usual, you're not even remotely capable of understanding the concepts.

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It's posts like the above which utterly remove the possibility of you having credibility. If you're going to throw around insults about free clinics, at least make sure your facts are straight first.

 

Wraith wrote that regression toward the mean is caused by a two part process. First, measurement error on the first test causes a distribution to appear to be more spread out than it really is. He compared this to the stretching of a rubber band. The second part of this process is when you re-measure those with the most extreme scores. On average, those scores will drift a little closer to the mean the second time around. This second part of the process is like the rubber band snapping back into its normal shape.

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Wraith stated in the quote that you are so fond of:

I may have missed it when he explicitely stated that measurement error is causing the regression towards the mean, but that doesn't seem to be what the argument is about here at all anymore.

 

...

 

EDIT: I liken it to someone saying that stretching a rubber band is causing it to snap back to it's original form. Yes, the displacement needs to occur for the snap back to occur, but the snap back is actually occuring because of the elasticity of the rubber band. Both are necessary. It seems to me to be, at least right now, an argument of semantics.

Your hero Wraith explicitly stated that if you are saying measurement error causes regression to the mean that you are wrong.

 

WHY would you use a metaphor that you claim to know is inaccurate / wrong?

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I think, when you post for all to see that "error causes a stretched rubber band to snap back", we don't need him to decide whether or not you understand him.  :)

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Thanks for making up random stuff, and putting words in my mouth. You're really adding to things here. No, really. Keep up the good work.

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Your hero Wraith explicitly stated that if you are saying measurement error causes regression to the mean that you are wrong.

 

WHY would you use a metaphor that you claim to know is inaccurate / wrong?

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I'm using the metaphor correctly. Measurement error causes the rubber band to stretch. Remeasuring those with the most extreme scores causes it to snap back into place.

 

Let me put it to you this way: suppose you had a group of people that all had an I.Q. of 100. You give them an I.Q. test. Some get lucky and get a 110, others get unlucky and get a 90, and still others get a 100 on the test. Measurement error is causing this group's I.Q.s to appear to be more spread out than they really are--like the stretching of a rubber band.

 

Next, you gather up those who scored a 90 on the I.Q. test, and ask them to take the test a second time. Some will once again get an unlucky 90; others will get lucky 110s; and still others will get correctly scored at 100. On average, this group's score on the second test will be 100. The rubber band snaps back into place.

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Because he is smart, and the rest of you are not.

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:)

 

I found one other Wraith quote from earlier in the discussion where he explicitly tells our friend HA that error does not cause regression to the mean.

So what exactly are you arguing for/against in this entire debate? What you've said is true, but not because measurement error is causing regression towards the mean but because both sample population and measurement error are normally distributed. What is the conflict about?

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But apparently that was before Wraith fully understood that saying error causes regression to the mean doesn't mean what it appears to mean due to some metaphorical allusion to something (unfortunately, I'm not smart enough to figure out what that something is).

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I'm using the metaphor correctly. Measurement error causes the rubber band to stretch. Remeasuring those with the most extreme scores causes it to snap back into place.

 

Let me put it to you this way: suppose you had a group of people that all had an I.Q. of 100. You give them an I.Q. test. Some get lucky and get a 110, others get unlucky and get a 90, and still others get a 100 on the test. Measurement error is causing this group's I.Q.s to appear to be more spread out than they really are--like the stretching of a rubber band.

 

Next, you gather up those who scored a 90 on the I.Q. test, and ask them to take the test a second time. Some will once again get an unlucky 90; others will get lucky 110s; and still others will get correctly scored at 100. On average, this group's score on the second test will be 100. The rubber band snaps back into place.

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:)

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I've just done some extensive research in the lab this afternoon. No matter what methodology i tried, using various measuring devices, such as a ruler, calipers, etc, i could not get measurement error to cause the rubber band to snap back when stretched out, nor could i get measurement error to make the rubber band stretch. So once again, Holcomb's arm is wrong, and we can add rubber band stretching to the endless list of things that he knows nothing about.

 

One thing my research did prove, however, is that since the rubber band cant talk, nor can it post on twobillsdrive, the rubber band does appear to be significantly smarter than the arm. In hours of research with the rubber band, it was never wrong.

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I found one other Wraith quote from earlier in the discussion where he explicitly tells our friend HA that error does not cause regression to the mean.

But apparently that was before Wraith fully understood that saying error causes regression to the mean doesn't mean what it appears to mean due to some metaphorical allusion to something (unfortunately, I'm not smart enough to figure out what that something is).

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Suppose someone scores 140 on an I.Q. test. This person is planning on taking the test a second time. At first glance, you'd think the person's expected score the second time around would be another 140. That isn't the case--the expected score on the retest will be somewhere in the 120s or 130s.

 

There are three possibilities here: a 140 score could indicate someone with an I.Q. of 140. It could indicate someone with a lower I.Q. (130 for example) who got lucky on the test. Or it could indicate someone with an I.Q. of 150 who got unlucky. Of these three possibilities, the second is far more likely than the third. Therefore, the average person who gets a 140 on an I.Q. test has an I.Q. that's less than 140. On average someone who gets a 140 on an I.Q. test will get a somewhat lower score upon being retested.

 

It took Wraith a while to realize that supposed statistics experts such as Bungee Jumper and Ramius were disputing this widely-known, non-controversial phenomenon. But once he realized what the argument was about, he took my side.

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It took Wraith a while to realize that supposed statistics experts such as Bungee Jumper and Ramius were disputing this widely-known, non-controversial phenomenon. But once he realized what the argument was about, he took my side.

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We're NOT arguing the effect, we're arguing that it's NOT caused by "measurement error", you idiot. It's caused by what we all - including Wraith - said: the normal distribution of scores about the mean. Extreme values in a normally distributed sample tend to be less extreme if measured again not because they're in error, but because they're extreme, and the probability distribution of the sample dictates that there's a VERY high probability of getting a lower value than an equivalent or higher value for a given extreme measure. AND THAT'S NOT ERROR, YOU !@#$ING IDIOT!!! Refer to my dice (plural, NOT a single die, which does NOT represent normally distributed probability, hence is not applicable) example, or ANY CREDIBLE STATISTICS SOURCE ON THE DAMN PLANET, YOU LOON!!!!! Like a textbook, maybe.

 

:)

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Thanks for making up random stuff, and putting words in my mouth. You're really adding to things here. No, really. Keep up the good work.

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You're right. You didn't say measurement error causes a rubber band to snap back. You said it causes the rubber band to stretch. Which is even more absurd. :)

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We're NOT arguing the effect, we're arguing that it's NOT caused by "measurement error", you idiot.  It's caused by what we all - including Wraith - said: the normal distribution of scores about the mean.  Extreme values in a normally distributed sample tend to be less extreme if measured again not because they're in error, but because they're extreme, and the probability distribution of the sample dictates that there's a VERY high probability of getting a lower value than an equivalent or higher value for a given extreme measure.  AND THAT'S NOT ERROR, YOU !@#$ING IDIOT!!!  Refer to my dice (plural, NOT a single die, which does NOT represent normally distributed probability, hence is not applicable) example, or ANY CREDIBLE STATISTICS SOURCE ON THE DAMN PLANET, YOU LOON!!!!!  Like a textbook, maybe. 

 

:)

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You're wrong. Take a ruler, and measure the height of everyone in the U.S. population. Use a nice, accurate ruler to avoid measurement error.

 

Now consider 100 people who measured 7'6". Put them in a room, and have them be remeasured. What's the expected value of the remeasurement? Right: 7'6". No regression toward the mean here.

 

Now keep the example the same, except that your measurement method allows you to be off by an inch. Someone who's initially measured at 7'6" might be a lucky 7'5", or an unlucky 7'7". Of those two possibilities, the 7'5" one is more likely, because there are more 7'5"s than 7'7"s. Someone who got measured at 7'6" the first time around will, on average, get a slightly shorter measurement upon being remeasured. The presence of measurement error is necessary for this form of regression toward the mean to occur.

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You're right.  You didn't say measurement error causes a rubber band to snap back.  You said it causes the rubber band to stretch.  Which is even more absurd.  :)

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Wraith's metaphor was a good one, but was only beneficial for those capable of understanding it.

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You're wrong. Take a ruler, and measure the height of everyone in the U.S. population. Use a nice, accurate ruler to avoid measurement error.

 

Now consider 100 people who measured 7'6". Put them in a room, and have them be remeasured. What's the expected value of the remeasurement? Right: 7'6". No regression toward the mean here.

 

Now keep the example the same, except that your measurement method allows you to be off by an inch. Someone who's initially measured at 7'6" might be a lucky 7'5", or an unlucky 7'7". Of those two possibilities, the 7'5" one is more likely, because there are more 7'5"s than 7'7"s. Someone who got measured at 7'6" the first time around will, on average, get a slightly shorter measurement upon being remeasured. The presence of measurement error is necessary for this form of regression toward the mean to occur.

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Except that that isn't any form of regression toward the mean, you dolt. :)

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Except that that isn't any form of regression toward the mean, you dolt.  :)

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Yes it is. Suppose an error-prone height measurement system. The average person who's initially measured at 7'6" will, upon being remeasured, appear to slightly regress toward the mean.

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