Group Comparisons Involving Zero-Inflated Count Data in Clinical Trials

• Togo Kanae

  Clinical Statistics

• Iwasaki Manabu

  Department of Computer and Information Science, Seikei University

Abstract

In clinical trials, outcomes of count data sometimes have excess zeros. When a test drug is compared to a control, zero-inflated data may be ignored or interest is taken only in the proportion of zero counts. By applying the two-part model, Lachenbruch (2001a) suggested a test statistic called the two-part statistic that combines the test statistics of the zero part and the non-zero part. The test for the zero part is the chi-square test. The test for the non-zero part may be a Wilcoxon test, a t-test, etc. This article proposes methods for calculating the sample size and power for the two-part statistic with zero-inflated Poisson data. We developed the methods of sample size and power for the two-part statistic using the Wilcoxon test adjusted for ties. The relationship between the non-zero part and zero-truncated Poisson distribution is also described. Furthermore, we examine the power of the two-part statistic, conventional methods, and the zero-inflated Poisson model.

Journal

• Japanese Journal of Biometrics

  Japanese Journal of Biometrics 34 (2), 53-66, 2014

  The Biometric Society of Japan

Keywords

• two-part statistic
• zero-inflated Poisson model
• Wilcoxon test adjusted for ties
• sample size
• power

Details

• CRID: 1390001204369351936
• NII Article ID: 130004721698
• NII Book ID: AA11591618
• DOI: 10.5691/jjb.34.53
• ISSN: 21856494
• ISSN: 09184430
• NDL BIB ID: 025352777
• Web Site: http://id.ndl.go.jp/bib/025352777
• Web Site: https://ndlsearch.ndl.go.jp/books/R000000004-I025352777
• Text Lang: ja
• Data Source:
  • JaLC
  • NDL
  • Crossref
  • CiNii Articles
• Abstract License Flag: Disallowed