calculatePhat: calculatePhat

In reproducer: Reproduce Statistical Analyses and Meta-Analyses

calculatePhat

Description

This function calculates the probability of superiority (i.e., Phat) and its confidence interval based on Brunner and Munzel (2000) heteroscedastic analog of WMW test. It is based on Wilcox'x bmp function with some amendments. It does not include a plotit facility. It uses the smallest non-zero variance to identify confidence intervals and statistical significance for values of Phat=0 and Phat=1. It ensure that confidence intervals do not take on invalid values such as values <0 or >1.

Usage

calculatePhat(x, y, alpha = 0.05, sigfig = -1)

Arguments

x	is a vector of values from group 1
y	is a vector of values from group 2
alpha	is the Type 1 error level for statistical tests
sigfig	is the number of significant digits. If sigfig>0 the data in x and y is truncated to the specified number of significant digits.

Value

list including the value of the t-test for PHat, the estimate of PHat and Cliff's d, and the confidence intervals for PHat.

Author(s)

Rand Wilcox amendments by Barbara Kitchenham and Lech Madeyski

Examples

x <- c(1.2, 3.0, 2.2, 4.0, 2.5, 3.0)
y <- c(3, 4.2, 4, 6, 7, 5.9)
reproducer:::calculatePhat(x, y)
# $test.stat
# [1] 6.381249
# $phat
# [1] 0.9305556
# $dhat
# [1] 0.8611111
# $sig.level
# [1] 0.0001191725
# $s.e.
# [1] 0.06747199
# $ci.p
# [1] 0.7783001 1.0000000
# $df
# [1] 9.148489
# Another example:
z <- c(1, 2, 3, 4)
y <- c(5, 6, 7, 8)
reproducer:::calculatePhat(z, y)
# $test.stat
# [1] 10.6066
# $phat
# [1] 1
# $dhat
# [1] 1
# $sig.level
# [1] 4.135921e-05
# $s.e.
# [1] 0.04419417
# $ci.p
# [1] 0.8918608 1.0000000
# $df
# [1] 6

reproducer documentation built on Oct. 18, 2023, 5:10 p.m.