param_informationRates

Parameter Description: Information Rates

internal

Design and analysis of confirmatory adaptive clinical trials with continuous, binary, and survival endpoints according to the methods described in the monograph by Wassmer and Brannath (2016) <doi:10.1007/978-3-319-32562-0>. This includes classical group sequential as well as multi-stage adaptive hypotheses tests that are based on the combination testing principle.

Friedrich Pahlke

rpact

Confirmatory Adaptive Clinical Trial Design and Analysis

Gernot Wassmer

Till Jensen

Stephen Schueuerhuis

Tobias Muetze

param_informationRates function

<dl><dt>informationRates</dt>
<dd>The information rates t_1, ..., t_kMax (that must be fixed prior to the trial),
default is <code>(1:kMax) / kMax</code>. For the weighted inverse normal design, the weights are derived
through w_1 = sqrt(t_1), and w_k = sqrt(t_k - t_(k-1)). For the weighted Fisher's combination test, the
weights (scales) are w_k = sqrt((t_k - t_(k-1)) / t_1) (see the documentation).</dd></dl>

Arguments

Parameter Description: Information Rates — param_informationRates

<dl>

<dt>informationRates</dt>
<dd>The information rates t_1, ..., t_kMax (that must be fixed prior to the trial),
default is <code>(1:kMax) / kMax</code>. For the weighted inverse normal design, the weights are derived
through w_1 = sqrt(t_1), and w_k = sqrt(t_k - t_(k-1)). For the weighted Fisher's combination test, the
weights (scales) are w_k = sqrt((t_k - t_(k-1)) / t_1) (see the documentation).</dd>

</dl>