Re: please help
Kelly wrote: I have the gage repeatability reproducibility(gage RR) analysis done on two instruments, what hyphoses test can I use to test that the repeatability variance(expected sigma values of repeatability) of the two instruments are significantly different form each other or to say one has a lower variance than the other. Any insight will be greatly appreciated. Thanks in advance for your help. One approach is to form the likelihood function in each case and to eliminate the nuisance parameters (the means) by marginalization. Although it is well known that marginalization by maximization will give misleading answers for both the location and precision of your estimate of the variances, I have shown how another method based on marginalization by the rule of product-sum can avoid the problems known to exist with respect to the former. (See _Fuzziness and Probability_ (ACG Press, 1995)). This method also avoids the assumptions of the Bayesian approach -- effectively a method of marginalization by integration -- which have been considered and rejected, and with good reason in my opinion, by those of the classical school. The product-sum method may be relatively easily implemented within an extensible stat package such as R, and I would be happy to apply my implementation of it to your problem if you would send me the two datasets. Essentially, once the nuisance parameters (the one or more means) are eliminated, what is left in each case is the (marginal) likelihood function of the variance, and one could effectively compare directly the plots of the two variance marginal likelihoods, and also, if need be, the likelihood function of the difference, to see how different this is from zero. This is not a classicist's answer, but tests of hypothesis and all that can be obviated if the likelihood function can be directly manipulated in the way I describe. This has been the whole point of the Bayesian method, except of course for the inadequate justification provided not only for its insistent subjectiveness, but also for treating model parameters as though they were random variables in their own right. Hope this is helpful. Regards, S. F. Thomas = Instructions for joining and leaving this list and remarks about the problem of INAPPROPRIATE MESSAGES are available at http://jse.stat.ncsu.edu/ =
Re: please help
On 10 Jun 2001 07:27:55 -0700, [EMAIL PROTECTED] (Kelly) wrote: I have the gage repeatability reproducibility(gage RR) analysis done on two instruments, what hyphoses test can I use to test that the repeatability variance(expected sigma values of repeatability) of the two instruments are significantly different form each other or to say one has a lower variance than the other. Any insight will be greatly appreciated. Thanks in advance for your help. I am not completely sure I understand, but I will make a guess. There is hardly any power for comparing two ANOVAs that are done on different samples, until you make strong assumptions about samples being equivalent, in various regards. If ANOVAs are on the same sample, then a CHOW test can be used on the improved prediction if one hypothesis consists of an extra d.f. of prediction. If ANOVAs are on separate samples, I wonder if you could compare the residual variances, by the simple variance ratio F-test -- well, you could do it, but I don't know what arguments should be raised against it, for your particular case. There are criteria resembling the CHOW test that are used less formally, for incommensurate ANOVAs (not the same predictors) - AKAIKE and others. If your measures are done on the same (exact) items, you might have a paired test. Instrument A gets closer values on how many of the measurements that are done. Finally, if you can do a bunch of separate experiments, you can test whether A or B does better in more than half of them. -- Rich Ulrich, [EMAIL PROTECTED] http://www.pitt.edu/~wpilib/index.html = Instructions for joining and leaving this list and remarks about the problem of INAPPROPRIATE MESSAGES are available at http://jse.stat.ncsu.edu/ =
Please help
My name is Adil Abubakar and i am a student.and seek help . I have a question if anyone can help, please respond to [EMAIL PROTECTED] Person A did research on a total of 4500 people and got the follwoing results Q How many hours do you spend on the web 0-7 8-15 15+ 18% 48% 34% Q. Do you read a privacy policy before signing on to a web site The answers were 1= Strongly Agree 2= Agree 3= Neutral 4= disagree 5= strongly disagree 9% 17% 20%32% 22% respectively Another person asked the the same questions from a 100 people and got the same results in % terms? Can it be shown via CI that the result is consitent with the expectations created by the previous survey? Also can it be argued that the subjects have been subjected to the questions before. can it be asserted with statiscal significance , that if the survey is repeated on at least 100 people the result will in the same proximity of the above survey?? any help ya'll can provide will be appreciated Just the need different methodlogies Thanking you in anticipation Adil Abubakar [EMAIL PROTECTED] = Instructions for joining and leaving this list and remarks about the problem of INAPPROPRIATE MESSAGES are available at http://jse.stat.ncsu.edu/ =
Re: Please help
I rather think the problem is not adequately defined; but that may merely reflect the fact that it's a homework problem, and homework problems often require highly simplifying assumptions in order to be addressed at all. See comments below. On Fri, 4 May 2001, Adil Abubakar wrote: My name is Adil Abubakar and i am a student and seek help. snip if anyone can help, please respond to [EMAIL PROTECTED] Person A did research on a total of 4500 people and got the following results: Q. 1. How many hours do you spend on the web? 0-7 8-15 15+ 18% 48% 34% Q. 2. Do you read a privacy policy before signing on to a web site? 1=Strongly Agree 2=Agree 3=Neutral 4=disagree 5=strongly disagree 9% 17% 20% 32%22% If this were a research situation, or intended to reflect practical realities, there would also be information about the relationship between the answers to Q. 1 and the answers to Q. 2. This information might be in the form of a two-way table of relative frequencies, or (with suitable simplifying assumptions on the variables represented by Q.1 and Q.2) as a ccorrelation coefficient. Without _some_ information about the joint distribution, I do not see how one can hope to address the questions posed below. Another person asked the same questions of 100 people and got the same results in % terms. Can it be shown via CI that the result is consistent with the expectations created by the previous survey? If the % results were indeed the same (so that all differences in corresponding %s were zero), it would not be necessary to use a CI (by which I presume you mean confidence interval) to show consistency. (HOWEVER, even identical % results do not imply consistency, unless at the same time the joint distribution were ALSO identical; and you do not report information on this point.) OTOH, if the results were merely similar but not identical, you would want some means of assessing the strength of evidence that resides in the empirical differences. That in turn depends on the assumptions you're willing to make about the two variables: do you insist on treating the responses as (ordered) categories, or would you be willing, at least pro tempore, to assign (e.g.) codes 1, 2, 3 to the responses to Q. 1, use the codes 1, 2, 3, 4, 5 supplied for Q. 2, and treat those values as though they represented approximately equal intervals? Also can it be argued that the subjects have been subjected to the questions before? Not sure what you mean by this question. If you know that the Ss have indeed been asked these questions previously (are they perhaps a subset of the original 4500?), no arguing is needed; although what this would imply about the results is unclear. If you mean, do the identical (or at least consistent) results imply that the Ss must have encountered these same questions previously, I do not see how that can be argued, at least not without more information than you've so far provided. Perhaps more to the point, why would such an argument be of interest? Can it be asserted with statistical significance, that if the survey is repeated on at least 100 people the result will [be] in the same proximity of the above survey?? No. I suggest you look closely at the definition of statistical significance: the term is quite incompatible with the assertion you propose. (If you don't see that, you might bring a focussed version of the question back to the list. If you do see that, you may still have some question that is more or less in the same ball-park as the question you've asked here, and you may wish to bring the revised question to our attention.) any help ... will be appreciated. Just need the different methodologies. Yes; but for which questions, exactly? -- DFB. Donald F. Burrill [EMAIL PROTECTED] 348 Hyde Hall, Plymouth State College, [EMAIL PROTECTED] MSC #29, Plymouth, NH 03264 603-535-2597 184 Nashua Road, Bedford, NH 03110 603-472-3742 = Instructions for joining and leaving this list and remarks about the problem of INAPPROPRIATE MESSAGES are available at http://jse.stat.ncsu.edu/ =
