test.welch | R Documentation |
This function performs Welch's two-sample t-test and Welch's ANOVA including Games-Howell post hoc test for multiple comparison and provides descriptive statistics, effect size measures, and a plot showing bars representing means for each group and error bars for difference-adjusted confidence intervals.
test.welch(formula, data, alternative = c("two.sided", "less", "greater"),
posthoc = FALSE, conf.level = 0.95, hypo = TRUE, descript = TRUE,
effsize = FALSE, weighted = FALSE, ref = NULL, correct = FALSE,
digits = 2, p.digits = 3, as.na = NULL, plot = FALSE, bar = TRUE,
point = FALSE, ci = TRUE, jitter = FALSE, adjust = TRUE,
point.size = 3, errorbar.width = 0.1, jitter.size = 1.25,
jitter.width = 0.05, jitter.height = 0, jitter.alpha = 0.1,
xlab = NULL, ylab = "y", ylim = NULL, ybreaks = ggplot2::waiver(),
title = NULL, subtitle = "Confidence Interval", filename = NULL,
width = NA, height = NA, units = c("in", "cm", "mm", "px"),
dpi = 600, write = NULL, append = TRUE, check = TRUE, output = TRUE)
formula |
a formula of the form |
data |
a matrix or data frame containing the variables in the
formula |
alternative |
a character string specifying the alternative hypothesis,
must be one of |
posthoc |
logical: if |
conf.level |
a numeric value between 0 and 1 indicating the confidence level of the interval. |
hypo |
logical: if |
descript |
logical: if |
effsize |
logical: if |
weighted |
logical: if |
ref |
a numeric value or character string indicating the reference group. The standard deviation of the reference group is used to standardized the mean difference to compute Cohen's d. |
correct |
logical: if |
digits |
an integer value indicating the number of decimal places to be used for displaying descriptive statistics and confidence interval. |
p.digits |
an integer value indicating the number of decimal places to be used for displaying the p-value. |
as.na |
a numeric vector indicating user-defined missing values,
i.e. these values are converted to |
plot |
logical: if |
bar |
logical: if |
point |
logical: if |
ci |
logical: if |
jitter |
logical: if |
adjust |
logical: if |
point.size |
a numeric value indicating the |
errorbar.width |
a numeric value indicating the horizontal bar width of the error bar. |
jitter.size |
a numeric value indicating the |
jitter.width |
a numeric value indicating the amount of horizontal jitter. |
jitter.height |
a numeric value indicating the amount of vertical jitter. |
jitter.alpha |
a numeric value between 0 and 1 for specifying the
|
xlab |
a character string specifying the labels for the x-axis. |
ylab |
a character string specifying the labels for the y-axis. |
ylim |
a numeric vector of length two specifying limits of the limits of the y-axis. |
ybreaks |
a numeric vector specifying the points at which tick-marks are drawn at the y-axis. |
title |
a character string specifying the text for the title of the plot. |
subtitle |
a character string specifying the text for the subtitle of the plot. |
filename |
a character string indicating the |
width |
a numeric value indicating the |
height |
a numeric value indicating the |
units |
a character string indicating the |
dpi |
a numeric value indicating the |
write |
a character string naming a text file with file extension
|
append |
logical: if |
check |
logical: if |
output |
logical: if |
By default, Cohen's d based on the non-weighted
standard deviation (i.e., weighted = FALSE
) which does not assume homogeneity
of variance is computed (see Delacre et al., 2021) when requesting an effect size
measure (i.e., effsize = TRUE
). Cohen's d based on the pooled standard
deviation assuming equality of variances between groups can be requested by
specifying weighted = TRUE
.
Returns an object of class misty.object
, which is a list with following
entries:
call |
function call |
type |
type of analysis |
sample |
type of sample, i.e., one-, two-, or paired sample |
data |
data frame with the outcome and grouping variable |
formula |
formula |
args |
specification of function arguments |
plot |
ggplot2 object for plotting the results |
result |
result table |
Takuya Yanagida takuya.yanagida@univie.ac.at
Rasch, D., Kubinger, K. D., & Yanagida, T. (2011). Statistics in psychology - Using R and SPSS. John Wiley & Sons.
Delacre, M., Lakens, D., Ley, C., Liu, L., & Leys, C. (2021). Why Hedges' g*s based on the non-pooled standard deviation should be reported with Welch's t-test. https://doi.org/10.31234/osf.io/tu6mp
test.t
, test.z
, test.levene
,
aov.b
, cohens.d
, ci.mean.diff
,
ci.mean
#----------------------------------------------------------------------------
# Two-Sample Design
# Example 1a: Two-sided two-sample Welch-test
test.welch(mpg ~ vs, data = mtcars)
# Example 1b: One-sided two-sample Welch-test
test.welch(mpg ~ vs, data = mtcars, alternative = "greater")
# Example 1c: Two-sided two-sample Welch-test, print Cohen's d
test.welch(mpg ~ vs, data = mtcars, effsize = TRUE)
# Example 1d: Two-sided two-sample Welch-test, plot results
test.welch(mpg ~ vs, data = mtcars, plot = TRUE)
#----------------------------------------------------------------------------
# Multiple-Sample Design
# Example 2a: Welch's ANOVA
test.welch(mpg ~ gear, data = mtcars)
# Example 2b: Welch's ANOVA, Games-Howell post hoc test
test.welch(mpg ~ gear, data = mtcars, posthoc = TRUE)
# Example 2c: Welch's ANOVA, print eta-squared and omega-squared
test.welch(mpg ~ gear, data = mtcars, effsize = TRUE)
# Example 2d: Welch's ANOVA, plot results
test.welch(mpg ~ gear, data = mtcars, plot = TRUE)
## Not run:
# Example 2e: Welch's ANOVA, save plot
test.welch(mpg ~ gear, data = mtcars, plot = TRUE,
filename = "Multiple-sample_Welch-test.png", width = 6, height = 5)
## End(Not run)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.