equivalence (version 0.8.2)

equiv.p: Inverts the regression-based TOST equivalence test

Description

This function generates the TOST intervals for the intercept and the slope of the regression of y on x, and determines the smallest region of indifference in each case that would reject the null hypothesis of dissimilarity.

Usage

equiv.p(x, y, alpha = 0.05)

Value

A list of two items:

Intercept

The smallest half-length of the interval that leads to rejection of the null hypothesis of dissimilarity for the intercept, in the units of y.

Slope

The smallest half-length of the interval that leads to rejection of the null hypothesis of dissimilarity for the slope, in the units of the slope.

Arguments

x

The predictor variable - perhaps the model predictions

y

The response variable - perhaps the observations

alpha

The size of the test

Author

Andrew Robinson

Details

The generated confidence intervals are corrected for experiment-level size of alpha using Bonferroni.

References

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

Robinson, A.P., R.A. Duursma, and J.D. Marshall. 2005. A regression-based equivalence test for model validation: shifting the burden of proof. Tree Physiology 25, 903-913.

See Also

tost.data

Examples

data(ufc)
equiv.p(ufc$Height.m.p, ufc$Height.m)