Landini Massimiliano wrote:
On Tue, 25 Jan 2005 15:42:45 +0100, you wrote:
|=[:o) Dear R users,
|=[:o)
|=[:o) Is it reasonable to transform data (measurements of plant height) to the
|=[:o) power of 1/4? I´ve used boxcox(response~A*B) and lambda was close to 0.25.
|=[:o)
IMHO (I'm far to be a statistician) no. I think that Box Cox procedure must be a
help to people that had none experience in data transforming. In fact data
transforming include other methods that Box Cox procedure can't perform as rank
transformation, arcsine square root percent transformation, hyperbolic inverse
sine, log-log, probit, normit and logit.
Transformation is not simply an application of a formula to massive data. Is
preferable decide appropriate transformation knowing deepening how and from
where data were collected.
|=[:o) Regards,
|=[:o) Christoph
|=[:o)
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Landini dr. Massimiliano
Tel. mob. (+39) 347 140 11 94
Tel./Fax. (+39) 051 762 196
e-mail: numero (dot) primo (at) tele2 (dot) it
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Why are you using a double square root transformation? Is the
transformation for the response variable? Transfromation is one way to
help insure that the error distribution is at least approximately
normal. So if this is the reason, it certainly could make sense. There
is no unique scale for making measurements. We choose a scale that helps
us analyze the data appropriately.
Rick B.
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