Tuesday, 22 September 2015

Analysis of ordinal data in ecology

The September Eco-Stats Lab (Friday 25th, 2pm, Bioscience level 6) will be on ordinal data analysis in ecology.

Ordered categorical data are commonplace in ecology when quantitative measurement of a variable of interest is not feasible or too costly. Examples include size of individuals, body condition and relative abundances of species. Cumulative link models are a powerful class of models for analyzing such data since observations are treated as categorical, the ordered nature is exploited and the flexible regression framework allows in-depth analyses.We will use the ordinal package in R to analyse some ecological ordinal data.

The code and details can be found here.

1 comment:

  1. A couple of comments:
    - while macroalgae looks on your plot like it doesn't fit the data, if you look at sample sizes:
    you find that it has small sample size so the deviation from expected may will be due to sampling variation. The fact that the residual plot didn't show up any huge outliers or deviations from one also supports this argument.

    - If you change the order the terms are added to the model, adding log(Size) first:
    fm1=clm(Mobility~log(Size), data=fish)
    you find that this explains most of what is going on. Diet is still significant but it explains much less of the deviance when added after Size than vice versa. i.e. the main story is that Mobility is relatd to Size, and effects of diet are more of a side-plot.