View source: R/compare_groups.R
nt_compare_mg | R Documentation |
Performing comparisons among three or more groups.
nt_compare_mg(
data,
group,
labels = NULL,
norm.test = helper_sf_test,
var.test = helper_levene_test,
qt.test = list(helper_anova, helper_welch_anova, helper_kruskal_wallis),
contrast = "Tukey",
alternative = "two.sided",
format = TRUE,
digits.p = 3,
digits.ci = 2,
save = FALSE,
file = "nt_compare_mg",
multiple.comparisons = FALSE
)
data |
a data frame with the variables. |
group |
a data frame with the group variable. |
labels |
a list of labels with components given by their variable names. |
norm.test |
a function with a numeric vector as input and a list as output containing an object named |
var.test |
a function with a numeric vector, group vector and paired logical variable as input and a list as output containing an object named |
qt.test |
a list of functions for three possible cases: (1) normality and homoscedasticity, (2) normality and heteroscedasticity, (3) non-normality and homoscedasticity/heteroscedasticity. |
contrast |
a matrix of contrasts. See more details in |
alternative |
a character value indicating the alternative hypothesis, must be one of "two.sided", "greater" or "less". |
format |
a logical value indicating whether the output should be formatted. |
digits.p |
the number of digits to present the p-values. |
digits.ci |
the number of digits to present the confidence intervals. |
save |
a logical value indicating whether the output should be saved as a csv file. |
file |
a character value indicating the name of output file in csv format to be saved. |
multiple.comparisons |
a logical value indicating if pairwise comparisons should be performed. |
If test = "automatic"
, the normality assumption will be verified by
norm.test
and homoscedasticity assumption will evaluate the assumption of
var.test
at a significance level of 0.05.
If the data satisfies both assumptions, then qt.test[[1]]
is chosen;
if only normality is satisfied, then qt.test[[2]]
; if only homoscedasticity
or neither assumptions, then qt.test[[3]]
.
data(iris)
iris |> nt_compare_mg(group = Species)
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