(Fixed the top posting, to preserve the context of my earlier post.) [EMAIL PROTECTED] wrote:
> "Gus Gassmann" <[EMAIL PROTECTED]> wrote in message > [EMAIL PROTECTED]">news:[EMAIL PROTECTED]... > > [EMAIL PROTECTED] wrote: > > > Gus, > > > > I am still not sure what you are doing. What is a bucket? > > The essence of > > what you seem to be claiming is that when we sample y to > > be uniform, then CR > > gives us the opposite results. You admit, however, that > > CR works with the > > usual approach. > > "Works" is a loaded word. I admit that when x1 and x2 are > sampled to be uniform > and you compute y = x1 + x2 and further compute the > correlation of y with x1 > both overall and over subsets of the x1 (lower, middle and > upper), the correlation > coefficients follow a predicted pattern. > > You seem to be playing the game "heads Gus wins, tails Bill > loses." There is nothing dishonest about what I am > saying. I describe a procedure that is very easy to do > with any spread sheet. The logic is there to support the > results. When you say "admit" perhaps you should say that > you see. > "See", "admit", it makes little difference. Note, however, that you were the first to use the word, and you wanted me to "admit that CR works". I want to find out whether it does or not. I have no axe to grind, no professional nose to get out of joint, no ego to bruise. Just an interest in the truth. > No one is guilty here and no one is winning. We are > scientists seeking truth, together. So you SEE that we can > differetiate the cause from the effect, assuming that > effects are combinations of causes... at least in > simulations and analyses as I describe them and as you have > replicated them. What you are seeing is what many people > before you have seen and gone on to dismiss by reference to > what they believe is my crazy personality or some other > nonsensical excuse for backing out when the results support > CR. I trust that you will not do that but I do not know if > any demonstration or logic is capable of convencing you of > the validity of CR. Can you be convinced or are you simply > trying to disprove me with out any concern for the truth? I > do not mean this offensively, but I do want to have some > sense of where this conversation is headed. > So, yes, I can be convinced, but for now I reserve judgment. > I am afraid that I still do not know what you did. > Remember, I am only a psychologist, not a mathematician. > Would you mind giving us a small data set and step by step > instructions, for example, as we might do with excel? I am > particularly concerned about the criteria you use to pick > sets of values. I do not see the point in your sampling > scheme since all we need to do is sort the variables by the > normally distributed ones and trim off all the data > corresponding to the upper and lower tails of the normal > distributions. This seems to be the most parsimonious > thing to do. Furthermore, when the normally distributed > variable is the hypthesized effect, we need not ever trim > the tails off. The effect is supposed to be triangular. > My point is that it should not matter how you choose the sample. I am a bit worried about trimming off the tails. The effect should be observable no matter what. But I'll grant you that maybe trimming the tails may enhance the effect or make it more visible. > It sounds to me that when you collect subsamples you are > selecting y values somehow so that you are building in > additional dependencies between the collected x values and > the y values. > This is impossible, like I said. When I construct y as the sum of x1 and x2, then y is the effect and x1 and x2 are the causes. This fact is not altered in the least by my decision to report only every tenth set of values, or every one hundredth, or any other subset. (At least in my definition of "cause". If you disagree on this point, then there is indeed no purpose in continuing.) Whether the causal effect is _visible_ or not is of course another matter. Maybe we should in fact get agreement on this point before I try to explain the sampling scheme to you again. (rest snipped.) . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
