[R] mult comp significance
Spencer Graves
spencer.graves at pdf.com
Thu Aug 3 13:07:10 CEST 2006
I read two questions: physical meaning and how to display only
significant differences.
PHYSICAL MEANING
A p value is the probability of obtaining by chance alone a result at
least as extreme as what we observe. A "simultaneous" or "adjusted" p
value is the probability that at least one of the multiple tests was at
least as extreme as what observed.
A (1-alpha) confidence interval or region is a random set that
includes the true but unknown value with probability at least (1-alpha).
A set of (1-alpha) simultaneous confidence intervals is a random set
in the multidimensional space that includes the true but unknown values
of all parameter comparisons with probability at least (1-alpha).
SELECTING ONLY SIGNIFICANT DIFFERENCES
Consider the following modification of the first example in the
"simint" help page:
library(multcomp)
data(recovery)
RecInts <- simint(minutes~blanket, data=recovery, type="Dunnett",
conf.level=0.9, alternative="less",eps=0.0001)
To see the structure of "RecInts", look at "str(RecInts)". This
indicates that "RecInts" is a list, and one of its components is a named
vector called "p.value.adj". This suggests we try the following:
> with(RecInts, p.value.adj[p.value.adj<0.05])
blanketb2-blanketb0
5.484862e-05
Hope this helps.
Spencer Graves
Nair, Murlidharan T wrote:
> This has a stats question and a R question. I am sure there are many
> core statisticians here how would know the answer to this simple
> question. In determining the significant comparisons using the methods
> in multcomp, the ones that are designated as significant are the ones
> that do not intersect the zero line. What is the physical meaning of
> this and why are those considered significant? I can sort those out and
> pick out by their adjusted pvalues to pick the top ones correct? Is
> there an method the multcomp that will output only the significant ones?
>
> Thanks ../Murli
>
>
>
>
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