liptak.ztest: Liptak weighted Z-test

In samvanderpoel/partial-pairs: Statistics for Partially Matched Samples

Description

liptak.ztest returns the p-value associated with Liptak's weighted z-test for partially matched pairs

Usage

liptak.ztest(x, y, alternative = c("two.sided", "greater", "less"))

Arguments

x	a non-empty numeric vector containing some NA values
y	a non-empty numeric vector containing some NA values
alternative	specification of the alternative hypothesis. Takes values: "two.sided", "greater", or "less".

Details

Liptak's weighted Z-test computes the p-values of a paired sample t-test on the n1 paired entries and of a two-sample t-test on the n2+n3 unpaired entries (see vignette for further details on the paired vs. unpaired distinction). The two p-values are then weighted and combined as detailed in [Kuan & Huang, 2013].

If proper sample size conditions are not met, then liptak.ztest may exit or perform a paired or unpaired two-sample t.test, depending on the nature of the sample size issue.

If the variance of input data is close to zero, liptak.ztest will return an error message.

Value

p-value associated with the hypothesis test

References

Kuan, Pei Fen, and Bo Huang. "A simple and robust method for partially matched samples using the p‐values pooling approach." Statistics in medicine 32.19 (2013): 3247-3259.

Examples

In the following, the true means are not equal:

x = rnorm(400, 0, 1)
x[sample(1:400, size=75, replace=FALSE)] = NA
y = rnorm(400, 0.4, 3)
y[sample(1:400, size=75, replace=FALSE)] = NA
liptak.ztest(x, y, alternative = 'two.sided')

samvanderpoel/partial-pairs documentation built on Dec. 22, 2021, 10:14 p.m.