Why we should use simpler models if the data allow this: relevance for ANOVA designs in experimental biology |
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Authors: | Stanley E Lazic |
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Institution: | (1) Department of Physiology, Development and Neuroscience, University of Cambridge, CB2 3DY, UK;(2) Centre for Brain Repair, University of Cambridge, CB2 2PY, UK |
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Abstract: | Background Analysis of variance (ANOVA) is a common statistical technique in physiological research, and often one or more of the independent/predictor
variables such as dose, time, or age, can be treated as a continuous, rather than a categorical variable during analysis –
even if subjects were randomly assigned to treatment groups. While this is not common, there are a number of advantages of
such an approach, including greater statistical power due to increased precision, a simpler and more informative interpretation
of the results, greater parsimony, and transformation of the predictor variable is possible. |
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Keywords: | |
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