Compute confidence interval
Compute a confidence interval around a summary statistic. Currently, only simulation-based methods are supported.
Learn more in vignette("infer").
get_confidence_interval( x, level = 0.95, type = "percentile", point_estimate = NULL ) get_ci(x, level = 0.95, type = "percentile", point_estimate = NULL)
x |
Data frame of calculated statistics or containing attributes of
theoretical distribution values. Currently, dependent on statistics being
stored in |
level |
A numerical value between 0 and 1 giving the confidence level. Default value is 0.95. |
type |
A string giving which method should be used for creating the
confidence interval. The default is |
point_estimate |
A numeric value or a 1x1 data frame set to |
A null hypothesis is not required to compute a confidence interval, but
including hypothesize() in a chain leading to get_confidence_interval()
will not break anything. This can be useful when computing a confidence
interval after previously computing a p-value.
A 1 x 2 tibble with 'lower_ci' and 'upper_ci' columns. Values correspond to lower and upper bounds of the confidence interval.
get_ci() is an alias of get_confidence_interval().
conf_int() is a deprecated alias of get_confidence_interval().
boot_distr <- gss %>%
# We're interested in the number of hours worked per week
specify(response = hours) %>%
# Generate bootstrap samples
generate(reps = 1000, type = "bootstrap") %>%
# Calculate mean of each bootstrap sample
calculate(stat = "mean")
boot_distr %>%
# Calculate the confidence interval around the point estimate
get_confidence_interval(
# At the 95% confidence level; percentile method
level = 0.95
)
# For type = "se" or type = "bias-corrected" we need a point estimate
sample_mean <- gss %>%
specify(response = hours) %>%
calculate(stat = "mean") %>%
dplyr::pull()
boot_distr %>%
get_confidence_interval(
point_estimate = sample_mean,
# At the 95% confidence level
level = 0.95,
# Using the standard error method
type = "se"
)
# More in-depth explanation of how to use the infer package
## Not run:
vignette("infer")
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