glance.equiv_change_mean {cmstatr} | R Documentation |
Glance at a equiv_change_mean
object
Description
Glance accepts an object of type equiv_change_mean
and returns a tibble::tibble()
with
one row of summaries.
Glance does not do any calculations: it just gathers the results in a tibble.
Usage
## S3 method for class 'equiv_change_mean'
glance(x, ...)
Arguments
x |
a |
... |
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 valuen_sample
passed to this function or the length of the vectordata_sample
. -
mean_sample
the mean of the observations in the sample for which equivalency is being checked. This is either the valuemean_sample
passed to this function or the mean of the vectordata-sample
. -
sd_sample
the standard deviation of the observations in the sample for which equivalency is being checked. This is either the valuemean_sample
passed to this function or the standard deviation of the vectordata-sample
. -
n_qual
the number of observations in the qualification data to which the sample is being compared for equivalency. This is either the valuen_qual
passed to this function or the length of the vectordata_qual
. -
mean_qual
the mean of the qualification data to which the sample is being compared for equivalency. This is either the valuemean_qual
passed to this function or the mean of the vectordata_qual
. -
sd_qual
the standard deviation of the qualification data to which the sample is being compared for equivalency. This is either the valuemean_qual
passed to this function or the standard deviation of the vectordata_qual
. -
modcv
logical value indicating whether the equivalency calculations were performed using the modified CV approach -
sp
the value of the pooled standard deviation. Ifmodecv = TRUE
, this pooled standard deviation includes the modification to the qualification CV. -
t0
the test statistic -
t_req
the t-value for\alpha / 2
anddf = n1 + n2 -2
-
threshold_min
the minimum value of the sample mean that would result in a pass -
threshold_max
the maximum value of the sample mean that would result in a pass -
result
a character vector of either "PASS" or "FAIL" indicating the result of the test for change in mean
See Also
Examples
x0 <- rnorm(30, 100, 4)
x1 <- rnorm(5, 91, 7)
eq <- equiv_change_mean(data_qual = x0, data_sample = x1, alpha = 0.01)
glance(eq)
## # A tibble: 1 x 14
## alpha n_sample mean_sample sd_sample n_qual mean_qual sd_qual modcv
## <dbl> <int> <dbl> <dbl> <int> <dbl> <dbl> <lgl>
## 1 0.01 5 85.8 9.93 30 100. 3.90 FALSE
## # ... with 6 more variables: sp <dbl>, t0 <dbl>, t_req <dbl>,
## # threshold_min <dbl>, threshold_max <dbl>, result <chr>