groupcompare (version 1.0.1)

bootstrap: Bootstrap for Various Statistics

Description

Conducts a bootstrap procedure to calculate confidence intervals for various statistics.

Usage

bootstrap(x, statistic, alternative="two.sided", alpha = 0.05, 
  Q = c(0.25, 0.5, 0.75), qt = 7, R = 3000)

Value

A list containing the data frames for the following components for each statistic:

normal

Lower and upper limits of the confidence interval computed with the normal method.

basic

Lower and upper limits of the confidence interval computed with the basic method.

percent

Lower and upper limits of the confidence interval computed with the percent method.

bca

Lower and upper limits of the confidence interval computed with the BCa method.

Arguments

x

A data frame or matrix containing the data.

statistic

Name of the function to compute the statistic of interest.

alternative

Type of hypothesis test. The default is "two.sided".

alpha

A numeric value specifying the significance level for confidence intervals. The default is 0.05.

Q

A numeric vector or a number specifying the probabilities used in quantile calculations. The default is c(0.25, 0.5, 0.75) for P25, P50, P75 (aka Q1, Q2 and Q3).

qt

A numeric value specifying the type of quantile calculation. The default is 7.

R

An integer specifying the number of bootstrap replicates. The default is 3000.

Author

Zeynel Cebeci, A. Firat Ozdemir, Engin Yildiztepe

Details

This function performs a bootstrap procedure to calculate confidence intervals for various statistics. It is mainly used to evaluate the differences between various statistics for two groups based on a specified function. The function calculates confidence intervals using different methods, including normal, basic, percentile, and bias-corrected and accelerated (BCa) intervals. It allows users to pass custom statistics (via statistic) that include parameters like quantiles (via Q) and types of quantiles (qt), making it versatile for non-standard use cases. In this way, the function extends the capabilities of boot::boot.ci (R's suggested package) by supporting more advanced statistical needs and customizable interval calculations. This function also incorporates the argument alternative can be set to "greater" or "less" for one-tailed confidence intervals, whereas boot::boot.ci primarily focuses on two-tailed intervals.Therefore, it is particularly useful for specialized applications. The data can be provided in long format, and the test uses a specified number of bootstrap replicates to calculate the empirical distribution of the test statistic under the null hypothesis.

See Also

permtest

Examples

# Load the quail dataset 
data(quail)

# Bootstrap for the difference of various basic statistics 
# Increase R for real-world applications

bootres <- bootstrap(quail, statistic = calcstatdif, R=200)
bootres

# Arrange the results as a data frame
ci2df(bootres)

# Bootstrap for the differences of quantiles 
bootresq <- bootstrap(quail, statistic = calcquantdif, R=200)
bootresq

# Arrange the results as a data frame
ci2df(bootresq)