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Robust non-parametric tests for complex-repeated measures problems in ophthalmology.
MedLine Citation:
PMID:  21705436     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
The NonParametric Combination methodology (NPC) of dependent permutation tests allows the experimenter to face many complex multivariate testing problems and represents a convincing and powerful alternative to standard parametric methods. The main advantage of this approach lies in its flexibility in handling any type of variable (categorical and quantitative, with or without missing values) while at the same time taking dependencies among those variables into account without the need of modelling them. NPC methodology enables to deal with repeated measures, paired data, restricted alternative hypotheses, missing data (completely at random or not), high-dimensional and small sample size data. Hence, NPC methodology can offer a significant contribution to successful research in biomedical studies with several endpoints, since it provides reasonably efficient solutions and clear interpretations of inferential results. Pesarin F. Multivariate permutation tests: with application in biostatistics. Chichester-New York: John Wiley &Sons, 2001; Pesarin F, Salmaso L. Permutation tests for complex data: theory, applications and software. Chichester, UK: John Wiley &Sons, 2010. We focus on non-parametric permutation solutions to two real-case studies in ophthalmology, concerning complex-repeated measures problems. For each data set, different analyses are presented, thus highlighting characteristic aspects of the data structure itself. Our goal is to present different solutions to multivariate complex case studies, guiding researchers/readers to choose, from various possible interpretations of a problem, the one that has the highest flexibility and statistical power under a set of less stringent assumptions. MATLAB code has been implemented to carry out the analyses.
Authors:
Chiara Brombin; Edoardo Midena; Luigi Salmaso
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2011-6-24
Journal Detail:
Title:  Statistical methods in medical research     Volume:  -     ISSN:  1477-0334     ISO Abbreviation:  -     Publication Date:  2011 Jun 
Date Detail:
Created Date:  2011-6-27     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9212457     Medline TA:  Stat Methods Med Res     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Affiliation:
Department of Management and Engineering, University of Padova, Padova, Italy.
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