Output a regression table with estimates and macro statistics — effect_metrics_one

The regression output comes from stats::lm. T-test is performed using stats::t.test. Normality check is performed using stats::shapiro.test. Equality of variances across groups is assessed using car::leveneTest. Cohen's d is calculated using effectsize::cohens_d.

Usage

effect_metrics_one_grouped(
  data,
  col,
  cross,
  method = "lm",
  labels = TRUE,
  clean = TRUE,
  ...
)

Arguments

data: A tibble.
col: The column holding metric values.
cross: The column holding groups to compare.
method: A character vector of methods, e.g. c("t.test","lm"). Supported methods are t.test (only valid if the cross column contains two levels) and lm (regression results).
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 list object containing volker tables with the requested statistics.

Examples

library(volker)
data <- volker::chatgpt

effect_metrics_one_grouped(data, sd_age, sd_gender)
#> 
#> 
#> |Term               | estimate| ci low| ci high| standard error|     t|     p| stars|
#> |:------------------|--------:|------:|-------:|--------------:|-----:|-----:|-----:|
#> |(Intercept)        |    37.52|  33.21|   41.84|           2.18| 17.24| 0.000|   ***|
#> |female (Reference) |         |       |        |               |      |      |      |
#> |male               |     3.69|  -1.88|    9.27|           2.81|  1.31| 0.192|      |
#> |diverse            |    -4.53| -32.18|   23.13|          13.94| -0.32| 0.746|      |
#> 
#> 
#> |Statistic                     | value|
#> |:-----------------------------|-----:|
#> |Adjusted R squared            |     0|
#> |Degrees of freedom            |     2|
#> |Residuals' degrees of freedom |    98|
#> |F                             |  0.98|
#> |p                             |  0.38|
#> |stars                         |      |