View source: R/non_directional_tests.R
get_absolute_es | R Documentation |
The function returns the average absolute effect size across participants. The function accepts a dataset in long format with specific columns: identifier ('idv'), independent and dependent variables (iv and dv, respectively). All levels of the independent variable must be included under each identifier.
get_absolute_es(
data,
idv = "id",
dv = "rt",
iv = "condition",
summary_function = lsr::cohensD
)
data |
The dataset to analyze. |
idv |
The name of the participant identifier column. |
dv |
The dependent variable to apply the summary function (summary_function) to. For multiple dependent variables use a string list with the names of each dependent variable (e.g., c('dv1','dv2')), |
iv |
Labels of an independent variable, indicating the different levels under which the dependent variable ('dv') is expected to differ. |
summary_function |
The summary function to apply to the dependent variables ('dv') as a function of the independent variable ('iv') for each participant ('idv'). |
A list including the results of the function
statistic - The average absolute effect size across all participants.
absolute_es_per_id - Absolute effect size for each participant.
[signcon::test_absolute_es()] which uses this function to test the significance of the group-level absolute effect size.
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