pairw.oneway | R Documentation |
Conducts all possible pairwise Welch tests with adjustments to P-values using methods from p.adjust
pairw.oneway(y, x, conf = 0.95, digits = 5, method = "holm")
y |
Response variable |
x |
Explanatory variable |
conf |
Confidence level |
digits |
Number of digits in results |
method |
Generalized method for controlling family wise type one error. These must be methods from |
The function pairw.oneway
and the confidence interval functions it calls return a list of class = "pairw"
.
1) the type of contrast (names are taken from levels in x),
2) the mean difference,
3) the lower confidence bound of the true mean difference,
4) the upper confidence bound of the true mean difference,
5) the hypothesis decision, given the prescribed significance level, and
6) the adjusted P-value.
Other invisible
objects include:
cont |
a vector of contrasts. |
conf |
The confidence level. |
band |
A two column matrix containing the lower and upper confidence bounds. |
Note that while P-values will be adjusted for simultaneous inference (unless method = "none"
), confidence interval width are generally not adjusted. In particular, CI widths correspond to Welch SEs and Satterthwaite t degrees of freedoms Thus they control for heteroscedasticity, however they do not control for family-wise levels of \alpha
unless method = "bonferroni"
, under which the restrictive confidence level 1 - (\alpha/2r)
is used, where r is the number of comparisons.
Ken Aho and Peter Eckert
Kutner, M. H., Nachtsheim, C. J., Neter, J., and Li., W (2005) Applied Linear Statistical Models, 5th edition. McGraw-Hill, Boston.
p.adjust
, pairw.anova
y <- rnorm(30)
x <- as.factor(c(rep(1,10), rep(2,10), rep(3, 10)))
p <- pairw.oneway(y,x)
p
plot(p)
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