I work with environmental measurements that represent ratios of things (i.e., flow: volume/time, concentrations: mass/volume) and not absolute values (e.g., weights, mass, length, number of individuals).
I understand that Compositional Data are those data that represent parts of a whole ---- like proportions and percentages that add up to a constant value like 1 or 100%, respectively ---- and that compositional data require special treatment when performing certain analysis like correlation (e.g., log-ratio transformation, CoDA).
Do measurements like 3 mg/L or 10 mg/kg (which would be equivalent to 3 and 10 ppm, respectively) represent compositional data? If so, should I be using CoDA for analyzing those data?
Hiram Sarabia
Measurements such as 3 mg/L or 10 mg/kg represent concentrations, which are ratios between mass (or amount) and volume (or mass), and are not compositional data by themselves. Compositional data typically represent parts of a whole or a total system, such as proportions or percentage shares that add up to a constant value (e.g., 1 or 100%). Examples of compositional data are the percentage shares of different components in a mixture, such as the percentages of different gases in the atmosphere or different species in an ecosystem.
However, concentrations like 3 mg/L or 10 mg/kg, although they represent ratios, are not compositional data because they do not represent parts of a whole system that must sum to a fixed value. They are measures of the specific concentration of certain substances in a given volume or mass.
CoDA (Compositional Data Analysis) is a specialized methodology used when data are truly compositional, meaning they are interdependent and their sum must be constant. For analyses dealing with concentrations like 3 mg/L or 10 mg/kg, it is usually unnecessary to use CoDA. In these cases, standard statistical techniques (such as regression or correlation) are adequate, whereas CoDA would be used if you have data representing parts of a whole system, such as percentage shares that sum to 100%.
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