The following methods and formulas are used for testing the difference between the test mean and the reference mean.

Term | Description |
---|---|

Sample mean for sequence i (for more information, go to Methods and formulas for common concepts used in Equivalence Test for a 2x2 Crossover Design) | |

n_{i} | Number of participants in sequence i |

S_{i} | Sample standard deviation of for sequence i |

By default, Minitab uses the following formula to calculate the 100(1 – α)% confidence interval (CI) for equivalence:

CI = [min(*C, D _{l}*), max(

where:

If you select the option to use the 100(1 – 2α)% CI, then the CI is given by the following formula:

CI = [*D _{l}, D_{u}*]

For a hypotheses of Test mean > reference mean or Test mean - reference mean > lower limit, the 100(1 – α)% lower bound is equal to *D _{L}*.

Term | Description |
---|---|

D | Difference between the test mean and the reference mean |

SE | Standard error |

δ_{1} | Lower equivalence limit |

δ_{2} | Upper equivalence limit |

v | Degrees of freedom |

α | The significance level for the test (alpha) |

t_{1-α, v} | Upper 1 – α critical value for a t-distribution with v degrees of freedom |

Let *t*_{1} be the t-value for the hypothesis, , and let *t*_{2} be the t-value for the hypothesis, , where is the difference between the mean of the test population and the mean of the reference population. By default, the t-values are calculated as follows:

For a hypothesis of Test mean > reference mean, *δ*_{1} = 0.

For a hypothesis of Test mean < reference mean, *δ *_{2} = 0.

Term | Description |
---|---|

D | Difference between the sample test mean and the sample reference mean |

SE | Standard error of the difference |

δ_{1} | Lower equivalence limit |

δ_{2} | Upper equivalence limit |

The probability, *P*_{H0}, for each null hypothesis (H_{0}) is given by the following:

H_{0} |
P-Value |
---|---|

Term | Description |
---|---|

Unknown difference between the mean of the test population and the mean of the reference population | |

δ_{1} | Lower equivalence limit |

δ_{2} | Upper equivalence limit |

v | Degrees of freedom |

T | t-distribution with v degrees of freedom |

t_{1} | t-value for the hypothesis |

t_{2} | t-value for the hypothesis |

For information on how the t-values are calculated, see the section on t-values.