In particular, did the confidence interval include more common numbers like 0 or 0.5 or 1? If you describe the application a bit (but still briefly), that information along with the confidence interval might elicit other useful comments.
hope this helps. spencer graves
p.s PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html. It might help you formulate your question in a way that might elicit more useful answers.
Landini Massimiliano wrote:
On Sun, 30 Jan 2005 17:47:31 -0500, you wrote:
<<<<<-----------------SNIP
|=[:o) >
|=[:o) > |=[:o) >
|=[:o) Why are you using a double square root transformation? Is the |=[:o) transformation for the response variable? Transfromation is one way to |=[:o) help insure that the error distribution is at least approximately |=[:o) normal. So if this is the reason, it certainly could make sense.
Are you sure that (data^0.25) had sense??? Coud you explain me which is the sense?? I know sense of boxcox exponents near zero when data are positively skewed and log(data) make it normally distributed, or all those case where variances grow proportionally to means or when i know that there are interaction effects that not follow additive model (AnOVa assumption);
I know 0.5 exponent (square root) [ as sqr(data) if all data differ from zero else sqr(data+.5) else Asconbe propose sqr(data +3/8) else Tukey & Freeman propose sqr(data)+sqr(data+1) particularly suitable when data domain is (0,2) ] for right skewed data, frequently applied to count-data or count-of-something-over -a -surface (bacteria, virus, nematode, lions) due to n*p*q (variance) is almost proportional to its mean (n*p) so AnOVa fundamental assumption is basically violated....
I know 1/3 exponent applied to count-of-something-in-a -volume...and so on...
What is worth is that i'm trying to ask to Christoph to sit down and think: what kind of number are these?? E.coli/mL?? ...so...i try cuberoot transformation and/or log transformation Timing of a slug vs snail speed race?? ...so..i think that inverse transformation it best.
BoxCox procedure have produced a fantastic implement that can help many people but (IMHO) none procedure can be superior than Ripley + Bates + other gurus experience. If you ask to those great statisticians how do you manage electrophoresis velocity they could respond with "data^-1 why......blah blah blah" If you push data in BoxCox algorithm it will respond with "-0.97847164..." Which answer had more sense??? I prefer -1
|=[:o) There is no unique scale for making measurements. We choose a scale that helps |=[:o) us analyze the data appropriately.
|=[:o) |=[:o) Rick B.
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