Computes the effect size for each control-test group pairing in idx.
The resampling bootstrap distribution of the effect size is then subjected
to Bias-corrected and accelerated bootstrap (BCa) correction.
The following effect sizes mean_diff, median_diff, cohens_d, hedges_g and cliffs_delta
are used for most plot types.
mean_diff(dabest_obj, perm_count = 5000)median_diff(dabest_obj, perm_count = 5000)
cohens_d(dabest_obj, perm_count = 5000)
hedges_g(dabest_obj, perm_count = 5000)
cliffs_delta(dabest_obj, perm_count = 5000)
cohens_h(dabest_obj, perm_count = 5000)
Returns a dabest_effectsize_obj list with 22 elements. The following are the elements contained within:
raw_data The tidy dataset passed to load() that was cleaned and altered for plotting.
idx The list of control-test groupings as initially passed to load().
delta_x_labels Vector containing labels for the x-axis of the delta plot.
delta_y_labels String label for the y-axis of the delta plot.
Ns List of labels for x-axis of the raw plot.
raw_y_labels Vector containing labels for the y-axis of the raw plot.
is_paired Boolean value determining if it is a paired plot.
is_colour Boolean value determining if there is a colour column for the plot.
paired Paired ("sequential" or "baseline") as initially passed to load().
resamples The number of resamples to be used to generate the effect size bootstraps.
control_summary Numeric value for plotting of control summary lines for float_contrast = TRUE.
test_summary Numeric value for plotting of control summary lines for float_contrast = TRUE.
ylim Vector containing the y limits for the raw plot.
enquo_x Quosure of x as initially passed to load().
enquo_y Quosure of y as initially passed to load().
enquo_id_col Quosure of id_col as initially passed to load().
enquo_colour Quosure of colour as initially passed to load().
proportional Boolean value as initially passed to load().
minimeta Boolean value as initially passed to load().
delta Boolean value as initially passed to load().
proportional_data List of calculations related to the plotting of proportion plots.
boot_result List containing values related to the calculation of the effect sizes,
bootstrapping and BCa correction.
baseline_ec_boot_result List containing values related to the calculation
of the effect sizes, bootstrapping and BCa correction for the baseline error
curve.
permtest_pvals List containing values related to the calculations of permutation
t tests and the corresponding p values, and p values for different types of effect sizes
and different statistical tests.
A dabest_obj created by loading in dataset along with other
specified parameters with the load() function.
The number of reshuffles of control and test labels to be performed for each p-value.
The plot types listed under here are limited to use only the following effect sizes.
Proportion plots offers only mean_diff and cohens_h.
Mini-Meta Delta plots offers only mean_diff.
The other plots are able to use all given basic effect sizes as listed in the Description.
# Loading of the dataset
data(non_proportional_data)
# Applying effect size to the dabest object
dabest_obj <- load(non_proportional_data,
x = Group, y = Measurement,
idx = c("Control 1", "Test 1")
)
dabest_obj.mean_diff <- mean_diff(dabest_obj)
# Printing dabest effectsize object
print(dabest_obj.mean_diff)
Run the code above in your browser using DataLab