Welchs's Many-To-One Comparison Test
Performs Welchs's t-test for multiple comparisons with one control.
welchManyOneTTest(x, ...)
## Default S3 method:
welchManyOneTTest(
x,
g,
alternative = c("two.sided", "greater", "less"),
p.adjust.method = p.adjust.methods,
...
)
## S3 method for class 'formula'
welchManyOneTTest(
formula,
data,
subset,
na.action,
alternative = c("two.sided", "greater", "less"),
p.adjust.method = p.adjust.methods,
...
)
## S3 method for class 'aov'
welchManyOneTTest(
x,
alternative = c("two.sided", "greater", "less"),
p.adjust.method = p.adjust.methods,
...
)x |
a numeric vector of data values, a list of numeric data vectors or a fitted model object, usually an aov fit. |
... |
further arguments to be passed to or from methods. |
g |
a vector or factor object giving the group for the
corresponding elements of |
alternative |
the alternative hypothesis.
Defaults to |
p.adjust.method |
method for adjusting p values
(see |
formula |
a formula of the form |
data |
an optional matrix or data frame (or similar: see
|
subset |
an optional vector specifying a subset of observations to be used. |
na.action |
a function which indicates what should happen when
the data contain |
For many-to-one comparisons in an one-factorial layout with normally distributed residuals and unequal variances Welch's t-test can be used. A total of m = k-1 hypotheses can be tested. The null hypothesis H_{i}: μ_0(x) = μ_i(x) is tested in the two-tailed test against the alternative A_{i}: μ_0(x) \ne μ_i(x), ~~ 1 ≤ i ≤ k-1.
This function is basically a wrapper function for
t.test(..., var.equal = FALSE). The p-values for the test
are calculated from the t distribution
and can be adusted with any method that is implemented in
p.adjust.methods.
A list with class "PMCMR" containing the following components:
a character string indicating what type of test was performed.
a character string giving the name(s) of the data.
lower-triangle matrix of the estimated quantiles of the pairwise test statistics.
lower-triangle matrix of the p-values for the pairwise tests.
a character string describing the alternative hypothesis.
a character string describing the method for p-value adjustment.
a data frame of the input data.
a string that denotes the test distribution.
Welch, B. L. (1947) The generalization of "Student's" problem when several different population variances are involved, Biometrika 34, 28–35.
Welch, B. L. (1951) On the comparison of several mean values: An alternative approach, Biometrika 38, 330–336.
set.seed(245) mn <- rep(c(1, 2^(1:4)), each=5) sd <- rep(1:5, each=5) x <- mn + rnorm(25, sd = sd) g <- factor(rep(1:5, each=5)) fit <- aov(x ~ g) shapiro.test(residuals(fit)) bartlett.test(x ~ g) anova(fit) summary(welchManyOneTTest(fit, alternative = "greater", p.adjust="holm"))
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.