Processes and converts a tidy dataset into the dabestr format. The output of this function is then used as an input for various procedural functions within dabestr to create estimation plots.
load(
data,
x,
y,
idx = NULL,
paired = NULL,
id_col = NULL,
ci = 95,
resamples = 5000,
colour = NULL,
proportional = FALSE,
minimeta = FALSE,
delta2 = FALSE,
experiment = NULL,
experiment_label = NULL,
x1_level = NULL
)
Returns a dabest_obj
list with 18 elements. The following are the elements contained within:
raw_data
The tidy dataset passed to load()
that was cleaned and altered for plotting.
proportional_data
List of calculations related to the plotting of proportion plots.
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 determining if proportion plots are being
produced.
minimeta
Boolean value determining if mini-meta analysis is conducted.
delta2
Boolean value determining if delta-delta analysis for
2 by 2 experimental designs is conducted.
idx
List of control-test groupings for which the
effect size will be computed for.
resamples
The number of resamples to be used to generate the effect size bootstraps.
is_paired
Boolean value determining if it is a paired plot.
is_colour
Boolean value determining if there is a specified colour column
for the plot.
paired
Paired ("sequential" or "baseline") as initially passed to load()
.
ci
Numeric value which determines the range of the confidence interval for effect size
and bootstrap calculations. Only accepts values between 0 to 100 (inclusive).
Ns
List of labels for x-axis of the rawdata swarm plot.
control_summary
Numeric value for plotting of control summary lines for float_contrast= TRUE.
test_summary
Numeric value for plotting of test summary lines for float_contrast = TRUE.
ylim
Vector containing the y limits for the rawdata swarm plot.
A tidy dataframe.
Column in data
that contains the treatment groups.
Column in data
that contains the measurement values.
List of control-test groupings for which the effect size will be computed for.
Paired ("sequential" or "baseline"). Used for plots for experiments with repeated-measures designs.
If "sequential", comparison happens between each measurement to the one directly preceding it. (control vs group i)
If "baseline", comparison happens between each group to a shared control. (group i vs group i+1)
Column in data
indicating the identity of the
datapoint if the data is tagged. Compulsory parameter if paired is TRUE.
Default 95. Determines the range of the confidence interval for effect size and bootstrap calculations. Only accepts values between 0 to 100 (inclusive).
The number of resamples to be used to generate the effect size bootstraps.
Column in data
that determines the groupings for colour of the
swarmplot as opposed to x
.
Boolean value determining if proportion plots are being produced.
Boolean value determining if mini-meta analysis is conducted.
Boolean value determining if delta-delta analysis for 2 by 2 experimental designs is conducted.
Experiment column name for delta-delta analysis.
String specifying the experiment label that is used to distinguish the experiment and the factors (being used in the plotting labels).
String setting the first factor level in a 2 by 2 experimental design.
# Loading in of the dataset
data(non_proportional_data)
# Creating a dabest object
dabest_obj <- load(
data = non_proportional_data, x = Group, y = Measurement,
idx = c("Control 1", "Test 1")
)
# Printing dabest object
print(dabest_obj)
Run the code above in your browser using DataLab