effect_metrics_items_cor {volker} | R Documentation |
Output correlation coefficients for items and one metric variable
Description
The correlation is calculated using stats::cor.test
.
Usage
effect_metrics_items_cor(
data,
cols,
cross,
method = "pearson",
labels = TRUE,
clean = TRUE,
...
)
Arguments
data |
A tibble containing item measures. |
cols |
Tidyselect item variables (e.g. starts_with...). |
cross |
The column holding metric values to correlate. |
method |
The output metrics, pearson = Pearson's R, spearman = Spearman's rho. |
labels |
If TRUE (default) extracts labels from the attributes, see codebook. |
clean |
Prepare data by data_clean. |
... |
Placeholder to allow calling the method with unused parameters from effect_metrics. |
Value
A volker table containing itemwise correlations:
If method = "pearson"
:
-
R-squared: Coefficient of determination.
-
n: Number of cases the calculation is based on.
-
Pearson's r: Correlation coefficient.
-
ci low / ci high: Lower and upper bounds of the 95% confidence interval.
-
df: Degrees of freedom.
-
t: t-statistic.
-
p: p-value for the statistical test, indicating whether the correlation differs from zero.
-
stars: Significance stars based on the p-value (*, **, ***).
If method = "spearman"
:
-
Spearman's rho is displayed instead of Pearson's r.
-
S-statistic is used instead of the t-statistic.
Examples
library(volker)
data <- volker::chatgpt
effect_metrics_items_cor(
data, starts_with("cg_adoption_adv"), sd_age
)