Statistics in Experimental Cerebrovascular Research: Comparison of More than Two Groups with a Continuous Outcome Variable
Author(s) -
Peter Schlattmann,
Ulrich Dirnagl
Publication year - 2010
Publication title -
journal of cerebral blood flow and metabolism
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.167
H-Index - 193
eISSN - 1559-7016
pISSN - 0271-678X
DOI - 10.1038/jcbfm.2010.95
Subject(s) - outcome (game theory) , a priori and a posteriori , statistics , statistical power , variable (mathematics) , statistical hypothesis testing , statistical analysis , research design , econometrics , computer science , mathematics , mathematical economics , epistemology , mathematical analysis , philosophy
A common setting in experimental cerebrovascular research is the comparison of more than two experimental groups. Often, continuous measures such as infarct volume, cerebral blood flow, or vessel diameter are the primary variables of interest. This article presents the principles of the statistical analysis of comparing more than two groups using analysis of variance (ANOVA). We will also explain post hoc comparisons, which are required to show which groups significantly differ once ANOVA has rejected the null hypothesis. Although statistical packages perform ANOVA and post hoc contrast at a key stroke, in this study, we use examples from experimental stroke research to reveal the simple math behind the calculations and the basic principles. This will enable the reader to understand and correctly interpret the readout of statistical packages and to help prevent common errors in the comparison of multiple means.
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