Description Usage Arguments Details Value Author(s) References See Also Examples
Calculates statistics for interlaboratory studies.
interlabstats
is a generic function.
interlabstats.formula
generates the statistics based on a
simple analysis of variance.
interlabstats.default
uses a suitable fitted model object,
currently either an lmeMod
or a rlmeMod
object,
and extracts the desired statistics from it.
1 2 3 4 5 6 7 | interlabstats(object, ...)
## Default S3 method:
interlabstats(object)
## S3 method for class 'formula'
{formula, data, subset}
## S3 method for class 'interlab'
interlabstatsprint(x, groups=TRUE, ...)
|
object |
for |
formula |
Formula of type |
data |
dataset containing the variables used in |
subset |
usual subset argument, passed to |
x |
object of class |
groups |
for |
... |
further arguments to be passed to the methods or to
|
By interlab.formula
, the estimated quantities are obtained from
a classical fixed effects Analysis of Variance.
A list containig
mean |
overall mean |
sigma |
within-group standard deviation |
siggroup |
between-group standard deviation |
repeatability |
standard error of a difference between measurements of the same lab |
reproducibility |
same, for different labs |
groups |
table, containing number of observations, mean and standard deviation for each group |
data |
the two relevant variables of the original data.frame |
call |
the call to the function |
method |
estimatrion method.
"classical" for |
Argumentx of print.interlab
:
x |
interlab object, as generated by |
groups |
Should group table be printed? |
... |
Further arguments passed to |
Werner A. Stahel, ETH Zurich
Stahel ...
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | data(d.perm)
dd <- d.perm[d.perm$section=="w.1",]
dd[dd$team=="A","perm.log"] <- dd[dd$team=="A","perm.log"] - 0.3
## otherwise, there is no between group variation
( r.cl <- interlabstats(perm.log~team, data=dd) )
print(r.cl, groups=FALSE)
## Mixed models: lme
require(lme4)
r.lme <- lmer(perm.log~(1|team), data=dd, na.action=na.omit)
summary(r.lme)
interlabstats(r.lme)
## robust
require(robustlmm)
r.rlme <- rlmer(perm.log~(1|team), data=dd, na.action=na.omit)
summary(r.rlme)
interlabstats(r.rlme)
|
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