This is an internal function which takes in a matrix that contains the error probabilities for different values of the test statistics T1.doublebar and T.doublebar and finds the pair of critical values (k1,k) for T1.doublebar and T.doublebar which satisfy the following: (i) have a Type I error rate of at most alpha; (ii) among pairs of critical values that cannot be improved, the critical values are most equitable, dividing the chance of false rejection as equally as possible between the events T1.doublebar>=k1 and T.doublebar>=k.

1 | ```
adaptive.test.critical.value.func(critmat, alpha = 0.05)
``` |

`critmat` |
Matrix that contains the error probabilities for different values of the test statistics T1.doublebar and T.doublebar that is produced by the function jointcrit |

`alpha` |
Significance level at which the test is conducted (alpha = 0.05). |

`t1` |
Critical value k1 for the test statistic T1.doublebar |

`t1plust2` |
Critical value k for the test statistic T.doublebar |

Small, D.S., Cheng, J., Halloran, M.E. and Rosenbaum, P.R. (2013). "Case Definition and Design Sensitivity." Journal of the American Statistical Association, 108, 1457-1468. See Section 5.1 of the paper.

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