cmstatr (version 0.9.3)

glance.basis: Glance at a basis object

Description

Glance accepts an object of type basis and returns a tibble::tibble() with one row of summaries for each basis value.

Glance does not do any calculations: it just gathers the results in a tibble.

Usage

# S3 method for basis
glance(x, include_diagnostics = FALSE, ...)

Value

A tibble::tibble() with the following columns:

• p the the content of the tolerance bound. Normally 0.90 or 0.99

• conf the confidence level. Normally 0.95

• distribution a string representing the distribution assumed when calculating the basis value

• modcv a logical value indicating whether the modified CV approach was used. Only applicable to pooling methods.

• n the sample size

• r the number of groups used in the calculation. This will be NA for single-point basis values

• basis the basis value

Arguments

x

a basis object

include_diagnostics

a logical value indicating whether to include columns for diagnostic tests. Default FALSE.

...

Additional arguments. Not used. Included only to match generic signature.

Details

For the pooled basis methods (basis_pooled_cv and basis_pooled_sd), the tibble::tibble() returned by glance will have one row for each group included in the pooling. For all other basis methods, the resulting tibble will have a single row.

If include_diagnostics=TRUE, there will be additional columns corresponding with the diagnostic tests performed. These column(s) will be of type character and will contain a "P" if the diagnostic test passed, a "F" if the diagnostic test failed, an "O" if the diagnostic test was overridden or NA if the test was not run (typically because an optional argument was not passed to the function that computed the basis value).

See Also

basis()

Examples

set.seed(10)
x <- rnorm(20, 100, 5)
b <- basis_normal(x = x)
glance(b)

## # A tibble: 1 x 7
##       p  conf distribution modcv     n r     basis
##                
## 1   0.9  0.95 Normal       FALSE    20 NA     92.0


glance(b, include_diagnostics = TRUE)

## # A tibble: 1 x 11
##        p  conf distribution modcv     n r     basis outliers_within…
##                  
##  1   0.9  0.95 Normal       FALSE    20 NA     92.0 NA
## # … with 3 more variables: between_batch_variability ,
## #   outliers , anderson_darling_normal