Abstract：
:We review and compare statistical methods for the analysis of in vivo tumor growth experiments. The methods most commonly used are deficient in that they have either low power or misleading type I error rates. We propose a set of multivariate statistical modeling methods that correct these problems, illustrating their application with data from a study of the effect of alpha-difluoromethylornithine on growth of the BT-20 human breast tumor in nude mice. All the methods find significant differences between the alpha-difluoromethylornithine dose groups, but recommended sample sizes for a subsequent study are much smaller with the multivariate methods. We conclude that the multivariate methods are preferable and present guidelines for their use.
journal_name
Cancer Resjournal_title
Cancer researchauthors
Heitjan DF,Manni A,Santen RJsubject
Has Abstractpub_date
1993-12-15 00:00:00pages
6042-50issue
24eissn
0008-5472issn
1538-7445journal_volume
53pub_type
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