glance.equiv_mean_extremum  R Documentation 
equiv_mean_extremum
objectGlance 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 class 'equiv_mean_extremum'
glance(x, ...)
x 
an equiv_mean_extremum object returned from

... 
Additional arguments. Not used. Included only to match generic signature. 
A onerow 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
equiv_mean_extremum()
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_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>
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