Adjusting for Multiplicity of Statistical Tests in the Analysis of Carcinogenicity Studies

✍ Scribed by J. F. Heyse; D. Rom

• Publisher: John Wiley and Sons
• Year: 1988
• Tongue: English
• Weight: 669 KB
• Volume: 30
• Category: Article
• ISSN: 0323-3847
• DOI: 10.1002/bimj.4710300802

✦ Synopsis

Because the evaiuation of rodent carcinogenicity studies involves performing a stat istical analysis at each tumor site encountered i t is important to undeistaud the extent to which this multiplicity affects the false positive rate. It is equally important to apply methods of accounting for this multiplicity in the analysis.

I n this paper we discuss one such method which involves calculating t h e overall significance level associated with P,, the most extreme isolated trend P-value observed among the tumor sites encountered. The method constructs the distribution of trend scores simultaneously for each tumor site using (L multiresponse randomization procedure. As such, i t recognizee the discrete nature of the data and incorporates inherent dependencis t h a t may exist between the tumor sites.

For small studies i t is possible to perform a complete rerandomization and compute an exact adjusted trend P-value. However, for moderate or large studies the need exists for approximations based on efficient reaampling plans. We report one such approximation proposed by Dr. John Tukey which involves correcting the exact Bonferroni upper bound. Also, we show t h a t the independence assumption used in methods proposed by MANTEL (1980) and MANTEL et al. (1982) seems to be a reasonable approximation for the study discussed in the present report. This result needs to be supportcd further using additional studies.