Literature DB >> 15938548

A power analysis of tests for paired lifetime data.

William J Owen1.   

Abstract

A power analysis is used to compare tests developed for a new lifetime model applicable for certain paired-data experiments. Two pivotal quantities are available for exact parametric testing of the equality of the marginal survival distributions. Here, the power of each test will be calculated to find the more powerful test. The analysis leads to an interesting scenario where the two power curves are quite similar and less powerful test may actually be preferred for pragmatic considerations.

Mesh:

Year:  2005        PMID: 15938548     DOI: 10.1007/s10985-004-0385-9

Source DB:  PubMed          Journal:  Lifetime Data Anal        ISSN: 1380-7870            Impact factor:   1.588


  3 in total

1.  A comparative study of tests for paired lifetime data.

Authors:  Zhu Wang; Hon Keung Tony Ng
Journal:  Lifetime Data Anal       Date:  2006-10-20       Impact factor: 1.588

2.  Phase II trial design with growth modulation index as the primary endpoint.

Authors:  Jianrong Wu; Li Chen; Jing Wei; Heidi Weiss; Rachel W Miller; John L Villano
Journal:  Pharm Stat       Date:  2018-11-20       Impact factor: 1.234

3.  Evaluation of Treatment Effect with Paired Failure Times in a Single-Arm Phase II Trial in Oncology.

Authors:  Matthieu Texier; Federico Rotolo; Michel Ducreux; Olivier Bouché; Jean-Pierre Pignon; Stefan Michiels
Journal:  Comput Math Methods Med       Date:  2018-01-11       Impact factor: 2.238

  3 in total

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