pvalue.TOST | R Documentation |

Calculates the *p*-value(s) of the TOST procedure via students *t*-distribution
given pe, CV and n.

pvalue.TOST(pe, CV, n, logscale = TRUE, theta1, theta2, design = "2x2", robust = FALSE, both = FALSE) pvalues.TOST(pe, CV, n, logscale = TRUE, theta1, theta2, design = "2x2", robust = FALSE, both = TRUE)

`pe` |
Observed point estimate of the T/R ratio or difference. |

`CV` |
In case of In case of cross-over studies this is the within-subject CV, in case of a parallel-group design the CV of the total variability. |

`n` |
Total number of subjects if given as scalar. |

`logscale` |
Should the data be used after log-transformation or on original scale? |

`theta1` |
Lower (bio-)equivalence limit. |

`theta2` |
Upper (bio-)equivalence limit. |

`design` |
Character string describing the study design. |

`robust` |
If set to |

`both` |
Indicates if both |

Returns the *p*-value(s).

Returns a vector with named elements `p.left`

, `p.right`

if arguments `pe`

and `CV`

are scalars, else a matrix with columns `p.left`

, `p.right`

.

`p.left`

gives the *p*-value of testing

` HA1: theta >= theta1`

and `p.right`

the *p*-value of testing

` HA2: theta <= theta2`

against their respective Nulls.

The formulas implemented cover balanced and unbalanced designs.

In case of argument `n`

given as n(total) and is not divisible by the number
of (sequence) groups the total sample size is partitioned to the (sequence)
groups to have small imbalance only. A message is given in such cases.

SAS procedure TTEST with the TOST option names p.left = Upper, p.right= Lower
according to the tail of the *t*-distribution to be used for obtaining the
*p*-values.

B. Lang, man page by D. Labes

Schuirmann DJ. *A comparison of the two one-sided tests procedure and the power approach for
assessing the equivalence of average bioavailability.* J Pharmacokin Biopharm. 1987;15:657–80. doi: 10.1007/BF01068419

Hauschke D, Steinijans V, Pigeot I. *Bioequivalence Studies in Drug Development.* Chichester: Wiley; 2007.

`CI.BE`

# Defaults: 2x2 crossover, log-transformation # BE acceptance limits 0.8 ... 1.25, usual dfs # interested in both p-values pvalues.TOST(pe = 0.95, CV = 0.3, n = 12) # gives the vector (named elements) # p.left p.right # 0.09105601 0.02250985 # i.e. 'left' hypothesis H01: theta<=theta1 can't be rejected # 'right' hypothesis H02: theta>=theta2 can be rejected # max. p-value only as 'overall' pvalue, preferred by Benjamin pvalue.TOST(pe = 0.912, CV = 0.333, n = 24) # should give 0.08777621, i.e., inequivalence can't be rejected # this is operationally identical to CI.BE(pe = 0.912, CV = .333, n = 24) # lower limit = 0.7766 outside 0.8 ... 1.25, i.e., inequivalence can't be rejected

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.