Output a table with distribution parameters

The table type depends on the number of selected columns:

• One metric column: see tab_metrics_one

• Multiple metric columns: see tab_metrics_items

Group comparisons:

• One metric column and one grouping column: see tab_metrics_one_grouped

• Multiple metric columns and one grouping column: see tab_metrics_items_grouped

• Multiple metric columns and multiple grouping columns: see tab_metrics_items_grouped_items (not yet implemented)

By default, if you provide two column selections, the second column is treated as categorical. Setting the metric-parameter to TRUE will call the appropriate functions for correlation analysis:

• Two metric columns: see tab_metrics_one_cor

• Multiple metric columns and one metric column: see tab_metrics_items_cor

• Two metric column selections: see tab_metrics_items_cor_items

Parameters that may be passed to specific metric functions:

• ci: Add confidence intervals for means or correlation coefficients.

• values: The output metrics, mean (m), the standard deviation (sd) or both (the default).

• digits: Tables containing means and standard deviations by default round values to one digit. Increase the number to show more digits

• method: By default, correlations are calculated using Pearson’s R. You can choose Spearman’s Rho with the methods-parameter.

• labels: Labels are extracted from the column attributes. Set to FALSE to output bare column names and values.

Usage

tab_metrics(data, cols, cross = NULL, metric = FALSE, clean = TRUE, ...)

Arguments

data

A data frame.

cols

A tidy column selection, e.g. a single column (without quotes) or multiple columns selected by methods such as starts_with().

cross

Optional, a grouping column (without quotes).

metric

When crossing variables, the cross column parameter can contain categorical or metric values. By default, the cross column selection is treated as categorical data. Set metric to TRUE, to treat it as metric and calculate correlations.

clean

Prepare data by data_clean.

...

Other parameters passed to the appropriate table function.

Value

A volker tibble.

Examples

library(volker)
data <- volker::chatgpt

tab_metrics(data, sd_age)
#> 
#> 
#> |Age    | value|
#> |:------|-----:|
#> |min    |    18|
#> |q1     |    27|
#> |median |    38|
#> |q3     |    52|
#> |max    |    68|
#> |mean   |  39.7|
#> |sd     |  13.8|
#> |n      |   101|