summary()
summarises the sampled data and provides the minimum, first
quartile, median, mean, third quartile, and maximum values for each category.
Usage
# S3 method for class 'cat_sample'
summary(object, option, ...)
Arguments
- object
an object of class
cat_sample
created by the function cat_sample_data.- option
character string with the name of the option.
- ...
Unused arguments, included only for future extensions of the function.
Value
A tibble
with the summary statistics.
See also
Other cat data helpers:
cat_add_data()
,
cat_get_data()
,
cat_sample_data()
,
cat_start()
Examples
# Create the elic_cat object for an elicitation process with three topics,
# four options, five categories and a maximum of six experts per topic
my_categories <- c("category_1", "category_2", "category_3",
"category_4", "category_5")
my_options <- c("option_1", "option_2", "option_3", "option_4")
my_topics <- c("topic_1", "topic_2", "topic_3")
my_elicit <- cat_start(categories = my_categories,
options = my_options,
experts = 6,
topics = my_topics) |>
cat_add_data(data_source = topic_1, topic = "topic_1") |>
cat_add_data(data_source = topic_2, topic = "topic_2") |>
cat_add_data(data_source = topic_3, topic = "topic_3")
#> ✔ <elic_cat> object for "Elicitation" correctly initialised
#> ✔ Data added to Topic "topic_1" from "data.frame"
#> ✔ Data added to Topic "topic_2" from "data.frame"
#> ✔ Data added to Topic "topic_3" from "data.frame"
# Sample data from Topic 1 for all options using the basic method
samp <- cat_sample_data(my_elicit,
method = "basic",
topic = "topic_1")
#> ✔ Data sampled successfully using "basic" method.
# Summarise the sampled data
summary(samp, option = "option_1")
#> # A tibble: 5 × 7
#> Category Min Q1 Median Mean Q3 Max
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 category_1 1.88e- 32 6.21e- 6 2.37e- 3 0.124 0.119 1.00
#> 2 category_2 0 1.37e-77 1.35e-19 0.0710 0.00175 0.974
#> 3 category_3 9.81e- 27 3.14e- 3 1.79e- 1 0.366 0.765 1
#> 4 category_4 3.91e-282 5.91e-25 5.58e- 4 0.139 0.113 1.00
#> 5 category_5 5.07e- 62 1.31e- 4 9.37e- 2 0.300 0.619 1.00