Description Usage Arguments Value See Also Examples
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 mean_diff()
.
The median difference, given by median_diff()
.
Cohen's d, given by cohens_d()
.
Hedges'
g, given by hedges_g()
.
Cliff's delta, given by
cliffs_delta()
.
1 2 3 4 5 6 7 8 9  mean_diff(x, ci = 95, reps = 5000, seed = 12345)
median_diff(x, ci = 95, reps = 5000, seed = 12345)
cohens_d(x, ci = 95, reps = 5000, seed = 12345)
hedges_g(x, ci = 95, reps = 5000, seed = 12345)
cliffs_delta(x, ci = 95, reps = 5000, seed = 12345)

x 
A 
ci 
float, default 95. The level of the confidence intervals produced.
The default 
reps 
integer, default 5000. The number of bootstrap resamples that will be generated. 
seed 
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. 
A dabest_effsize
object with 10 elements.
data
The dataset passed to dabest(), as a
tibble
.
x
and y
The columns in data
used to plot the x
and y axes, respectively, as supplied to dabest(). These are
quoted variables for
tidy evaluation during the
computation of effect sizes.
idx
The vector of controltest groupings as initially passed to dabest().
is.paired
Whether or not the experiment consists of paired (aka repeated) observations. Originally supplied to dabest().
id.column
If is.paired
is TRUE
, the column in
data
that indicates the pairing of observations. As passed to
dabest().
effect.size
The effect size being computed. One of the
following: c("mean_diff", "median_diff", "cohens_d", "hedges_g",
"cliffs_delta")
.
.data.name
The variable name of the dataset passed to dabest().
summary
A tibble with a row for the mean or median of
each group in the x
column of data
, as indicated in
idx
.
result
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
(FALSE
)?
The effect size of the difference between the two groups.
The variable whose difference is being computed, ie. the
column supplied to y
.
The 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.
The effsize
package, which
is used under the hood to compute Cohen's d, Hedges' g, and
Cliff's delta.
The boot()
and boot.ci()
functions from the boot
package, which generate the (nonparametric)
bootstrapped resamples used to compute the confidence intervals.
1 2 3 4 5 6 7 8 9 10 11 
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