A new method for correlation analysis of compositional (environmental) data – a worked example

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F17%3A73582563" target="_blank" >RIV/61989592:15310/17:73582563 - isvavai.cz</a>

Result on the web

<a href="https://www.sciencedirect.com/science/article/pii/S0048969717314675" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0048969717314675</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.scitotenv.2017.06.063" target="_blank" >10.1016/j.scitotenv.2017.06.063</a>

Result language

angličtina

Original language name

A new method for correlation analysis of compositional (environmental) data – a worked example

Original language description

Most data in environmental sciences and geochemistry are compositional. Already the unit used to report the data (e.g., μg/l, mg/kg,wt%) implies that the analytical results for each element are not free to vary independently of the other measured variables. This is often neglected in statistical analysis, where a simple log-transformation of the single variables is insufficient to put the data into an acceptable geometry. This is also important for bivariate data analysis and for correlation analysis, for which the data need to be appropriately log-ratio transformed. A newapproach based on the isometric log-ratio (ilr) transformation, leading to so-called symmetric coordinates, is presented here. Summarizing the correlations in a heat-map gives a powerful tool for bivariate data analysis. Here an application of the new method using a data set from a regional geochemical mapping project based on soil O and C horizon samples is demonstrated. Differences to ‘classical’ correlation analysis based on log-transformed data are highlighted. The fact that some expected strong positive correlations appear and remain unchanged even following a log-ratio transformation has probably led to the misconception that the special nature of compositional data can be ignored when working with trace elements. The example dataset is employed to demonstrate that using ‘classical’ correlation analysis and plotting XY diagrams, scatterplots, based on the original or simply log-transformed data can easily lead to severe misinterpretations of the relationships between elements.

Czech name

—

Czech description

—

Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

10103 - Statistics and probability

Project

—

Continuities

N - Vyzkumna aktivita podporovana z neverejnych zdroju

Publication year

2017

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Science of the Total Environment

ISSN

0048-9697

e-ISSN

—

Volume of the periodical

607-608

Issue of the periodical within the volume

DEC

Country of publishing house

NL - THE KINGDOM OF THE NETHERLANDS

Number of pages

7

Pages from-to

965-971

UT code for WoS article

000408755300096

EID of the result in the Scopus database

—