inftocor

<code>inftocor()</code> transforms information (fractions) into correlation matrix.

It is often challenging to strongly control the family-wise type-1 error rate in the group-sequential trials with multiple endpoints (hypotheses). The inflation of type-1 error rate comes from two sources (S1) repeated testing individual hypothesis and (S2) simultaneous testing multiple hypotheses. The 'MultiGroupSequential' package is intended to help researchers to tackle this challenge. The procedures provided include the sequential procedures described in Luo and Quan (2023) <doi:10.1080/19466315.2023.2191989> and the graphical procedure proposed by Maurer and Bretz (2013) <doi:10.1080/19466315.2013.807748>. Luo and Quan (2013) describes three procedures, and the functions to implement these procedures are (1) seqgspgx() implements a sequential graphical procedure based on the group-sequential p-values; (2) seqgsphh() implements a sequential Hochberg/Hommel procedure based on the group-sequential p-values; and (3) seqqvalhh() implements a sequential Hochberg/Hommel procedure based on the q-values. In addition, seqmbgx() implements the sequential graphical procedure described in Maurer and Bretz (2013).

Xiaodong Luo

MultiGroupSequential

Group-Sequential Procedures with Multiple Hypotheses

Hui Quan

Sanofi 

inftocor function

<dl><dt>ir</dt>
<dd>Numeric vector of the sequence of information fractions. All
elements should be between 0 and 1 with the last one being exactly 1.</dd></dl>

Arguments

Author

Transform information fractions into correlation matrix — inftocor

<dl>

<dt>ir</dt>
<dd>Numeric vector of the sequence of information fractions. All
elements should be between 0 and 1 with the last one being exactly 1.</dd>

</dl>

inftocor: Transform information fractions into correlation matrix

Description

Usage

Value

Arguments

Author

Examples