Volume 42, Issue 3 (9-2018)                   Research in Medicine 2018, 42(3): 144-153 | Back to browse issues page

XML Persian Abstract Print

Deputy of Research and Technology, The Iranian Ministry of Health and Medical Education , s.noorb@gmail.com
Abstract:   (432 Views)
Background:One of the most important questions at the first steps of designing a laboratory animal research
is “How many animals do we need?”. In fact, the number of animals used, acts like a “double-edged sword”,
directly affecting the scientific power and ethicalness of a research. Therefore, proper sample size calculation
(SSC) is of outmost importance.
Methods: The aim of the present article is to teach methods of SSC. At first, a thorough understanding of basic
parameters used for SSC will be developed for readers. Then, the philosophy of SSC will be discussed. Next,
we will review the methods of calculating the number of Experimental Units for each type of studies and we
will explore a range of available tools to perform the calculations. Methods of spreading the proper number
of experimental units across the groups will be discussed and we will finally calculate the required number of
animals based on the number of experimental units, group compositions, and the likelihood of animals exiting
the study.
Results: Two main methods of SSC for animal research, i.e. Power Analysis and Resource Equation, are
presented with the emphasis on the ethical principles of sample size reduction. Pros and cons of each method
are discussed and a spreadsheet is provided for readers to perform routine calculations.
Conclusion: The number of animals used can considerably affect various aspects of a study, though, proper
determination of it does not follow a strict rule. For an optimum determination, researchers should have a
good understanding in statistics and laboratory animal science and be familiar with ethical principles and
sound scientific judgement.
Full-Text [PDF 653 kb]   (142 Downloads)    
Type of Study: Review |
Received: 2018/06/22 | Accepted: 2018/07/21 | Published: 2018/10/1