| load {dabestr} | R Documentation |
Loading data with dabestr
Description
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.
Usage
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
)
Arguments
data |
A tidy dataframe. |
x |
Column in |
y |
Column in |
idx |
List of control-test groupings for which the effect size will be computed for. |
paired |
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) |
id_col |
Column in |
ci |
Default 95. Determines the range of the confidence interval for effect size and bootstrap calculations. Only accepts values between 0 to 100 (inclusive). |
resamples |
The number of resamples to be used to generate the effect size bootstraps. |
colour |
Column in |
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. |
experiment |
Experiment column name for delta-delta analysis. |
experiment_label |
String specifying the experiment label that is used to distinguish the experiment and the factors (being used in the plotting labels). |
x1_level |
String setting the first factor level in a 2 by 2 experimental design. |
Value
Returns a dabest_obj list with 18 elements. The following are the elements contained within:
-
raw_dataThe tidy dataset passed toload()that was cleaned and altered for plotting. -
proportional_dataList of calculations related to the plotting of proportion plots. -
enquo_xQuosure of x as initially passed toload(). -
enquo_yQuosure of y as initially passed toload(). -
enquo_id_colQuosure of id_col as initially passed toload(). -
enquo_colourQuosure of colour as initially passed toload(). -
proportionalBoolean value determining if proportion plots are being produced. -
minimetaBoolean value determining if mini-meta analysis is conducted. -
delta2Boolean value determining if delta-delta analysis for 2 by 2 experimental designs is conducted. -
idxList of control-test groupings for which the effect size will be computed for. -
resamplesThe number of resamples to be used to generate the effect size bootstraps. -
is_pairedBoolean value determining if it is a paired plot. -
is_colourBoolean value determining if there is a specified colour column for the plot. -
pairedPaired ("sequential" or "baseline") as initially passed toload(). -
ciNumeric value which determines the range of the confidence interval for effect size and bootstrap calculations. Only accepts values between 0 to 100 (inclusive). -
NsList of labels for x-axis of the rawdata swarm plot. -
control_summaryNumeric value for plotting of control summary lines for float_contrast= TRUE. -
test_summaryNumeric value for plotting of test summary lines for float_contrast = TRUE. -
ylimVector containing the y limits for the rawdata swarm plot.
Examples
# 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)