Format

Send to

Choose Destination
See comment in PubMed Commons below
BMC Physiol. 2008 Jul 21;8:16. doi: 10.1186/1472-6793-8-16.

Why we should use simpler models if the data allow this: relevance for ANOVA designs in experimental biology.

Author information

1
Department of Physiology, Development and Neuroscience, University of Cambridge, CB2 3DY, UK. stan.lazic@cantab.net

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.

RESULTS:

An example is given from an experiment where rats were randomly assigned to receive either 0, 60, 180, or 240 mg/L of fluoxetine in their drinking water, with performance on the forced swim test as the outcome measure. Dose was treated as either a categorical or continuous variable during analysis, with the latter analysis leading to a more powerful test (p = 0.021 vs. p = 0.159). This will be true in general, and the reasons for this are discussed.

CONCLUSION:

There are many advantages to treating variables as continuous numeric variables if the data allow this, and this should be employed more often in experimental biology. Failure to use the optimal analysis runs the risk of missing significant effects or relationships.

PMID:
18644134
PMCID:
PMC2496911
DOI:
10.1186/1472-6793-8-16
[Indexed for MEDLINE]
Free PMC Article
PubMed Commons home

PubMed Commons

0 comments
How to join PubMed Commons

    Supplemental Content

    Full text links

    Icon for BioMed Central Icon for PubMed Central
    Loading ...
    Support Center