A simulation-based sample size calculation method for pre-clinical tumor xenograft experiments

Jianrong Wu, Shengping Yang

Research output: Contribution to journalArticlepeer-review


Pre-clinical tumor xenograft experiments usually require a small sample size that is rarely greater than 20, and data generated from such experiments very often do not have censored observations. Many statistical tests can be used for analyzing such data, but most of them were developed based on large sample approximation. We demonstrate that the type-I error rates of these tests can substantially deviate from the designated rate, especially when the data to be analyzed has a skewed distribution. Consequently, the sample size calculated based on these tests can be erroneous. We propose a modified signed log-likelihood ratio test (MSLRT) to meet the type-I error rate requirement for analyzing pre-clinical tumor xenograft data. The MSLRT has a consistent and symmetric type-I error rate that is very close to the designated rate for a wide range of sample sizes. By simulation, we generated a series of sample size tables based on scenarios commonly expected in tumor xenograft experiments, and we expect that these tables can be used as guidelines for making decisions on the numbers of mice used in tumor xenograft experiments.

Original languageEnglish
Pages (from-to)437-450
Number of pages14
JournalJournal of Biopharmaceutical Statistics
Issue number3
StatePublished - May 4 2018

Bibliographical note

Funding Information:
The first author’s work was supported in part by the National Cancer Institute support grant P30CA021765 and ALSAC.

Publisher Copyright:
© 2018, © 2018 Taylor & Francis Group, LLC.


  • Log-normal distribution
  • modified singed log-likelihood ratio test
  • pre-clinical
  • sample size calculation
  • tumor xenograft experiment

ASJC Scopus subject areas

  • Statistics and Probability
  • Pharmacology
  • Pharmacology (medical)


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