summary method for class "specr.setup". Provides a short summary of the created specifications (the "multiverse") that lists all analytic choices, prints the function used to extract the parameters from the model. Finally, if print.specs = TRUE, it also shows the head of the actual specification grid.

# S3 method for specr.setup
summary(object, digits = 2, rows = 6, print.specs = TRUE, ...)

Arguments

object

An object of class "specr.setup", usually, a result of a call to setup.

digits

The number of digits to use when printing the specification table.

rows

The number of rows of the specification tibble that should be printed.

print.specs

Logical value; if TRUE, a head of the specification tibble is returned and printed.

...

further arguments passed to or from other methods (currently ignored).

Value

A printed summary of an object of class specr.setup.

See also

The function setup(), which creates the "specr.setup" object.

Examples

# Setup specifications
specs <- setup(data = example_data,
  x = c("x1", "x2"),
  y = c("y1", "y2"),
  model = c("lm", "glm"),
  controls = c("c1", "c2", "c3"),
  subsets = list(group3 = unique(example_data$group3)))

# Summarize specifications
summary(specs)
#> Setup for the Specification Curve Analysis
#> -------------------------------------------
#> Class:                      specr.setup -- version: 1.0.1 
#> Number of specifications:   256 
#> 
#> Specifications:
#> 
#>   Independent variable:     x1, x2 
#>   Dependent variable:       y1, y2 
#>   Models:                   lm, glm 
#>   Covariates:               no covariates, c1, c2, c3, c1 + c2, c1 + c3, c2 + c3, c1 + c2 + c3 
#>   Subsets analyses:         C, B, A, all 
#> 
#> Function used to extract parameters:
#> 
#>   function (x) 
#> broom::tidy(x, conf.int = TRUE)
#> <environment: 0x7fefb7dfb4f0>
#> 
#> 
#> Head of specifications table (first 6 rows):
#> 
#> # A tibble: 6 × 7
#>   x     y     model controls      subsets group3 formula     
#>   <chr> <chr> <chr> <chr>         <chr>   <fct>  <glue>      
#> 1 x1    y1    lm    no covariates C       C      y1 ~ x1 + 1 
#> 2 x1    y1    lm    no covariates B       B      y1 ~ x1 + 1 
#> 3 x1    y1    lm    no covariates A       A      y1 ~ x1 + 1 
#> 4 x1    y1    lm    no covariates all     NA     y1 ~ x1 + 1 
#> 5 x1    y1    lm    c1            C       C      y1 ~ x1 + c1
#> 6 x1    y1    lm    c1            B       B      y1 ~ x1 + c1