cmstatr (version 0.9.3)

glance.equiv_change_mean: 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 equiv_change_mean
glance(x, ...)

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.

• mean_sample the mean of the observations in the sample for which equivalency is being checked. This is either the value mean_sample passed to this function or the mean of the vector data-sample.

• sd_sample the standard deviation of the observations in the sample for which equivalency is being checked. This is either the value mean_sample passed to this function or the standard deviation of the vector data-sample.

• n_qual the number of observations in the qualification data to which the sample is being compared for equivalency. This is either the value n_qual passed to this function or the length of the vector data_qual.

• mean_qual the mean of the qualification data to which the sample is being compared for equivalency. This is either the value mean_qual passed to this function or the mean of the vector data_qual.

• sd_qual the standard deviation of the qualification data to which the sample is being compared for equivalency. This is either the value mean_qual passed to this function or the standard deviation of the vector data_qual.

• modcv logical value indicating whether the equivalency calculations were performed using the modified CV approach

• sp the value of the pooled standard deviation. If modecv = TRUE, this pooled standard deviation includes the modification to the qualification CV.

• t0 the test statistic

• t_req the t-value for \(\alpha / 2\) and \(df = n1 + n2 -2\)

• 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

Arguments

x

a equiv_change_mean object returned from equiv_change_mean()

...

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

See Also

equiv_change_mean()

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
##                              
## 1  0.01        5        85.8      9.93     30      100.    3.90 FALSE
## # ... with 6 more variables: sp , t0 , t_req ,
## #   threshold_min , threshold_max , result