boot_ci_mean: Bootstrapped confidence interval of the mean

In DesiQuintans/desiderata: Assorted utility functions

Bootstrapped confidence interval of the mean

Description

Quick confidence interval calculation using bootstrapping, which makes no assumptions about the distribution of the data.

Usage

boot_ci_mean(vec, conf = 0.95, R = 999, type = "perc")

Arguments

vec	(Numeric) The numeric vector to calculate a CI for.
conf	(Double) The confidence level, by default 0.95 (95% CI).
R	(Integer) Number of bootstrap repetitions.
type	(Character) Either "perc" (percentile method, default) or "bca" (bias-corrected and accelerated method).

Details

By default, this is calculated using the percentile method, but it also supports the Bias-Corrected and Accelerated (BCA) method (DOI: 10.1080/01621459.1987.10478410), which is useful if you want to show that the lower and upper bounds of a statistic are asymmetric around the point estimate.

Value

A list with three items: ci_lwr contains the lower bound, ci_est contains the point estimate, and ci_upr contains the upper bound. If you are using this inside a dataframe, look at dplyr::unnest() to split this list out into columns.

Authors

• Desi Quintans (http://www.desiquintans.com)

Examples

set.seed(12345)
nums <- c(rnorm(10), NA_real_)

nums

## [1]  0.5855288  0.7094660 -0.1093033 -0.4534972  0.6058875 -1.8179560  0.6300986
## [8] -0.2761841 -0.2841597 -0.9193220         NA

boot_ci_mean(nums)

## $ci_lwr
## [1] -0.6455236
##
## $ci_est
## [1] -0.1329441
##
## $ci_upr
## [1] 0.3430405

# Demonstration of unnesting into a dataframe
# library(dplyr)
# library(tidyr)
#
# iris %>%
#     group_by(Species) %>%
#     summarise(mean_boot = boot_ci_mean(Petal.Length)) %>%
#     unnest(mean_boot, names_sep = ".")

## # A tibble: 3 × 4
##   Species    mean_boot.ci_lwr mean_boot.ci_est mean_boot.ci_upr
##   <fct>                 <dbl>            <dbl>            <dbl>
## 1 setosa                 1.41             1.46             1.51
## 2 versicolor             4.13             4.26             4.39
## 3 virginica              5.40             5.55             5.7

DesiQuintans/desiderata documentation built on April 9, 2023, 5:43 a.m.