Abstract
Correlation studies are an important hypothesis-generating and testing tool, and have a wide range of applications in many scientific fields. In ecological studies in particular, multiple environmental variables are often measured in an attempt to determine relationships between chemical, physical and biological factors. For example, one may wish to know whether and how soil properties correlate with plant physiology. Although correlation coefficients are widely used, their properties and limitations are often imperfectly understood. This is especially the case when one is interested in correlations between, say, trace element content in sediments and in marine organisms, where no one-to-one correspondence exists. We show that evaluating Pearson's correlation coefficient for either site-specific means or composite samples results in biased estimates, and we propose an alternative estimator. We use simulation studies to demonstrate that our estimator generally has a much smaller bias and mean squared error. We further illustrate its use in a case study of the correlation between trace element content in sediments and in mussels in Lyttelton Harbour, New Zealand.
| Original language | English |
|---|---|
| Pages (from-to) | 371-387 |
| Number of pages | 17 |
| Journal | Australian and New Zealand Journal of Statistics |
| Volume | 59 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - Dec. 2017 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 14 Life Below Water
Keywords
- Pearson's correlation coefficient
- analysis of variance and covariance
- ecological science
- mixed models
- mussels
- sediment
- toxicity
- trace elements
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