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equivalence (version 0.7.2)

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)

Arguments

x
The predictor variable - perhaps the model predictions
y
The response variable - perhaps the observations
alpha
The size of the test

Value

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.

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

Run this code

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

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