For each pair of observations in a
dabest object, a desired effect
size can be computed. Currently there are five effect sizes available:
The mean difference, given by
The median difference, given by
Cohen's d, given by
g, given by
Cliff's delta, given by
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float, default 95. The level of the confidence intervals produced.
integer, default 5000. The number of bootstrap resamples that will be generated.
integer, default 12345. This specifies the seed used to set the random number generator. Setting a seed ensures that the bootstrap confidence intervals for the same data will remain stable over separate runs/calls of this function. See set.seed for more details.
dabest_effsize object with 10 elements.
The dataset passed to dabest(), as a
The vector of control-test groupings as initially passed to dabest().
Whether or not the experiment consists of paired (aka repeated) observations. Originally supplied to dabest().
TRUE, the column in
data that indicates the pairing of observations. As passed to
The effect size being computed. One of the
c("mean_diff", "median_diff", "cohens_d", "hedges_g",
The variable name of the dataset passed to dabest().
A tibble with a row for the mean or median of
each group in the
x column of
data, as indicated in
A tibble with the following 15 columns:
The name of the control group and test group respectively.
The number of observations in the control group and test group respectively.
The effect size used.
Is the difference paired (
TRUE) or not
The effect size of the difference between the two groups.
The variable whose difference is being computed, ie. the
column supplied to
ci passed to this function.
The lower and upper limits of the Bias Corrected and Accelerated bootstrap confidence interval.
The lower and upper limits of the percentile bootstrap confidence interval.
The vector of bootstrap resamples generated.
Loading data for effect size computation.
Generating estimation plots after effect size computation.
The mathematical definitions and equations used to compute each effect size.
effsize package, which
is used under the hood to compute Cohen's d, Hedges' g, and
functions from the
boot package, which generate the (nonparametric)
bootstrapped resamples used to compute the confidence intervals.
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