multi_boot_standard: Nonparemetric bootstrap and empirical central tendency for...

In langcog/langcog: Language and Cognition Lab Things

Nonparemetric bootstrap and empirical central tendency for data frames

Description

Computes CI of bootstrapped mean of univariate data. NOTE: Bootstrapping functions will be computed over the grouping variables currently specified for the data frame.

Usage

multi_boot_standard(data, col, na.rm = FALSE, empirical_function,
  statistics_functions, nboot = 1000)

Arguments

data	A data frame.
col	A string indicating the column of data to bootstrap
na.rm	A logical indicating whether NAs should be dropped before bootstrapping (defaults to NULL)
empirical_function	Deprecated.
statistics_functions	Deprecated.
nboot	The number of bootstrap samples to take (defaults to 1000).

Examples

## Mean and 95% confidence interval for 1000 samples from two different normal distributions
require(dplyr)
gauss1 <- data_frame(value = rnorm(1000, mean = 0, sd = 1), condition = 1)
gauss2 <- data_frame(value = rnorm(1000, mean = 2, sd = 3), condition = 2)
df <- bind_rows(gauss1, gauss2) %>% group_by(condition)
df %>% multi_boot_standard(col = "value")

langcog/langcog documentation built on March 28, 2024, 9:52 a.m.