equivalence (version 0.7.2)

ptte.data: Computes a paired t-test for equivalence from a single sample of a normally-distributed population

Description

This function computes the test and key test quantities for the paired t-test for equivalence, as documented in Wellek (2003, pp 77-80). This function computes the test from a sample of a normally-distributed population.

Usage

ptte.data(x, alpha = 0.05, Epsilon = 0.25)

Arguments

x

paired differences

alpha

test size

Epsilon

magnitude of region of similarity

Value

A list with the following components

Dissimilarity

the outcome of the test of the null hypothesis of dissimilarity

Mean

the mean of the sample

StdDev

the standard deviation of the sample

n

the sample size

alpha

the size of the test

missing

the number of observations missing

Epsilon

the magnitude of the region of similarity

cutoff

the critical value

Tstat

the test statistic; if Tstat < cutoff then the null hypothesis is rejected.

Power

the power of the test evaluated at the observed value

Details

This test requires the assumption of normality of the population. Under that assumption the test is the uniformly most powerful invariant test (Wellek, 2003, pp. 78-79).

The function as documented by Wellek (2003) uses units relative to the standard deviation, noting (p. 12) that 0.25 corresponds to a strict test and 0.5 to a liberal test.

References

Robinson, A.P., and R.E. Froese. 2004. Model validation using equivalence tests. Ecological Modelling 176, 349--358.

Wellek, S. 2003. Testing statistical hypotheses of equivalence. Chapman and Hall/CRC. 284 pp.

See Also

ptte.stat, tost.data

Examples

data(ufc)
ptte.data(ufc$Height.m.p - ufc$Height.m)