Description Usage Arguments Details Value References Examples

This class implements Student's t-test for superiority and non-inferiority
tests.
A trial with continuous outcomes of the two groups `E`

and `C`

is assumed.
If `alternative == "greater"`

the null hypothesis for the
mean difference
Δ = μ_{E} - μ_{C}
is

H_{0}: Δ ≤ -δ_{NI} vs. H_{1}: Δ > -δ_{NI}.

`alternative=="smaller"`

, the direction of the effect is changed.
The function `setupStudent`

creates an object of class
`Student`

that can be used for sample size recalculation.

1 2 3 4 5 6 7 8 9 10 | ```
setupStudent(
alpha,
beta,
r = 1,
delta,
delta_NI = 0,
alternative = c("greater", "smaller"),
n_max = Inf,
...
)
``` |

`alpha` |
One-sided type I error rate. |

`beta` |
Type II error rate. |

`r` |
Allocation ratio between experimental and control group. |

`delta` |
Difference of effect size between alternative and null hypothesis. |

`delta_NI` |
Non-inferiority margin. |

`alternative` |
Does the alternative hypothesis contain greater
( |

`n_max` |
Maximal overall sample size. If the recalculated sample size
is greater than |

`...` |
Further optional arguments. |

The nuisance parameter is the variance
σ^{2}.
Within the blinded sample size recalculation procedure, it is re-estimated by
the one-sample variance estimator that is defined by

σ^{2}_{est} := 1/(n_{1}-1) ∑_{j=T,C} ∑_{k=1,...,n1,j} (x_{j,k} - x)^{2},

The following methods are available for this class:
`toer`

, `pow`

, `n_dist`

,
`adjusted_alpha`

, and `n_fix`

.
Check the design specific documentation for details.

An object of class `Student`

.

Lu, K. (2019). Distribution of the two-sample t-test statistic following blinded sample size re-estimation. Pharmaceutical Statistics 15(3): 208-215.

1 2 | ```
d <- setupStudent(alpha = .025, beta = .2, r = 1, delta = 3.5, delta_NI = 0,
alternative = "greater", n_max = 156)
``` |

```
```

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