Glance accepts an object of type equiv_mean_extremum and returns a tibble::tibble with one row of summaries.

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

# S3 method for equiv_mean_extremum
glance(x, ...)

Arguments

x

an equiv_mean_extremum object returned from equiv_mean_extremum

...

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

Value

A one-row tibble::tibble with the following columns:

alpha

the value of alpha passed to this function

n_sample

the number of observations in the sample for which equivalency is being checked. This is either the value n_sample passed to this function or the length of the vector data_sample.

modcv

logical value indicating whether the acceptance thresholds are calculated using the modified CV approach

threshold_min_indiv

The calculated threshold value for minimum individual

threshold_mean

The calculated threshold value for mean

result_min_indiv

a character vector of either "PASS" or "FAIL" indicating whether the data from data_sample passes the test for minimum individual. If data_sample was not supplied, this value will be NULL

result_mean

a character vector of either "PASS" or "FAIL" indicating whether the data from data_sample passes the test for mean. If data_sample was not supplied, this value will be NULL

min_sample

The minimum value from the vector data_sample. if data_sample was not supplied, this will have a value of NULL

mean_sample

The mean value from the vector data_sample. If data_sample was not supplied, this will have a value of NULL

See also

Examples

x0 <- rnorm(30, 100, 4) x1 <- rnorm(5, 91, 7) eq <- equiv_mean_extremum(data_qual = x0, data_sample = x1, alpha = 0.01) glance(eq)
#> # A tibble: 1 x 9 #> alpha n_sample modcv threshold_min_i… threshold_mean result_min_indiv #> <dbl> <int> <lgl> <dbl> <dbl> <chr> #> 1 0.01 5 FALSE 88.5 95.5 FAIL #> # … with 3 more variables: result_mean <chr>, min_sample <dbl>, #> # mean_sample <dbl>
## # A tibble: 1 x 9 ## alpha n_sample modcv threshold_min_indiv threshold_mean ## <dbl> <int> <lgl> <dbl> <dbl> ## 1 0.01 5 FALSE 86.2 94.9 ## # ... with 4 more variables: result_min_indiv <chr>, result_mean <chr>, ## # min_sample <dbl>, mean_sample <dbl>