Access the full text.
Sign up today, get DeepDyve free for 14 days.
A. Dmitrienko, W. Offen, P. Westfall (2003)
Gatekeeping strategies for clinical trials that do not require all primary effects to be significantStatistics in Medicine, 22
R. Marcus, Peritz Eric, K. Gabriel (1976)
On closed testing procedures with special reference to ordered analysis of varianceBiometrika, 63
Nornadiah Razali, Y. Wah (2011)
Power comparisons of Shapiro-Wilk , Kolmogorov-Smirnov , Lilliefors and Anderson-Darling tests
A. Akhtar (2015)
The Flaws and Human Harms of Animal ExperimentationCambridge Quarterly of Healthcare Ethics, 24
W. Russell, R. Burch (1960)
The Principles of Humane Experimental TechniqueMedical Journal of Australia, 1
A. Dmitrienko, A. Tamhane (2007)
Gatekeeping procedures with clinical trial applicationsPharmaceutical Statistics, 6
S. Holm (1979)
A Simple Sequentially Rejective Multiple Test ProcedureScandinavian Journal of Statistics, 6
Paula Johnson, D. Besselsen (2002)
Practical aspects of experimental design in animal research.ILAR journal, 43 4
Christine Jones, Arthur Thompson, Reg England (1970)
Printed in Great Britain
J. Aguilar-Nascimento (2005)
Fundamental steps in experimental design for animal studies.Acta Cirurgica Brasileira, 20
F. Bretz, W. Maurer, W. Brannath, M. Posch (2009)
A graphical approach to sequentially rejective multiple test proceduresStatistics in Medicine, 28
A. Dmitrienko, B. Wiens, A. Tamhane, Xin Wang (2007)
Tree‐structured gatekeeping tests in clinical trials with hierarchically ordered multiple objectivesStatistics in Medicine, 26
M. Festing, D. Altman (2002)
Guidelines for the design and statistical analysis of experiments using laboratory animals.ILAR journal, 43 4
B. Mayer, R. Muche (2013)
Die limitierte Aussagekraft formaler Fallzahlplanung im Rahmen von Tierversuchen der medizinischen GrundlagenforschungTierärztliche Praxis K: Kleintiere/Heimtiere, 41
Veronika Richter, R. Muche, B. Mayer (2018)
How much confidence do we need in animal experiments? Statistical assumptions in sample size estimationJournal of Applied Animal Welfare Science, 21
M. Festing
How to Reduce the Number of Animals Used in Research by Improving Experimental Design and Statistics
K. Muralidharan (2015)
Sample Size Determination
E. Glimm, W. Maurer, F. Bretz (2010)
Hierarchical testing of multiple endpoints in group‐sequential trialsStatistics in Medicine, 29
G. Hommel (1988)
A stagewise rejective multiple test procedure based on a modified Bonferroni testBiometrika, 75
J. Eng
Sample Size Estimation : How Many Individuals Should Be Studied ?
Z. Šidák (1967)
Rectangular Confidence Regions for the Means of Multivariate Normal DistributionsJournal of the American Statistical Association, 62
J. Kimmelman, J. Mogil, U. Dirnagl (2014)
Distinguishing between Exploratory and Confirmatory Preclinical Research Will Improve TranslationPLoS Biology, 12
W. Gaus (2015)
Interpretation of Statistical Significance - Exploratory Versus Confirmative Testing in Clinical Trials, Epidemiological Studies, Meta-Analyses and Toxicological Screening (Using Ginkgo biloba as an Example)Clinical and Experimental Pharmacology, 5
O. Dunn (1961)
Multiple Comparisons among MeansJournal of the American Statistical Association, 56
B. Mayer, R. Muche, Volume, Issue, Jan
International Journal of Biological & Medical Research Chances and Obstacles of Pilot Projects in Animal Research for Statistical Sample Size Calculation A* a Original Article International Journal of Biological and Medical Research Www.biomedscidirect.com Int J Biol Med Res
A. Dmitrienko, B. Millen, T. Brechenmacher, G. Paux (2011)
Development of gatekeeping strategies in confirmatory clinical trialsBiometrical Journal, 53
A. Dmitrienko, A. Tamhane, Xin Wang, Xun Chen (2006)
Stepwise Gatekeeping Procedures in Clinical Trial ApplicationsBiometrical Journal, 48
Statistical sample size calculation is essential when planning animal experiments in basic medical research. Usually, such trials involve the testing of multiple hypotheses, and interpreting them in a confirmative manner would require the appropriate adjustment of the Type 1 error. This has to be taken into account as early as possible during sample size estimation — otherwise, all the results obtained would be exploratory, i.e. without cogency. In this paper, the concept of gatekeeping is introduced, along with alternative approaches for Type 1 error adjustment. The application of gatekeeping to the calculation of sample size is demonstrated by using data sets from case studies. Overall, the evaluation of these examples showed that gatekeeping is able to keep the required number of animals comparatively small. In contrast to exploratory planning, which led to the lowest sample sizes, gatekeeping suggested a mean increase of 12% in sample size, while conservative Bonferroni adjustment raised the sample size by 34% on average. Gatekeeping is a prominent strategy for handling the multiple testing problem, and has been proven to keep the required sample sizes in animal studies comparatively low. Therefore, it is a suitable approach to a compromise between the Three Rs principle of reduction and the appropriate handling of the multiplicity issue in animal trials with a confirmative focus.
Alternatives to Laboratory Animals – SAGE
Published: Dec 1, 2017
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.