Visual Basic - IF THEN Usage in ArcGis Field Calculator

Recently I had to do some statistics on a numerical field in an attribute table and I had to classify this field according to a set of intervals for this purpose. I had to learn that there is no tool for this. So I had to use the fieldcalculator with the appropiate IF THEN VBA-Syntax:

Here is how it can be done (one of many ways):

Fit Sigmoid Curve with Confidence Intervals

Sigmoid curve fitting for transpiration measurements from porometer at different water potentials (pressure):

Adonis (PERMANOVA) - Assumptions

Before you use PERMANOVA (R-vegan function adonis) you should read the user notes for the original program by the author (Marti J. Anderson) who first came up with this method. An important assumtption for PERMANOVA is same "multivariate spread" among groups, which is similar to variance homogeneity in univariate ANOVA.

I'll show why you may draw the wrong conclusions if this assumption is not met:

Permutation Test with Stratified Data and Repeated Measurements

This is an example for a permutation test on stratified samples with repeated measurements. Samples are interdependent firstly because they come from several sites and secondly because the sampling was repeated a second time. That is samples of the same sites are dependent and sample t1 and sample t2, taken from the very same places are dependent. 

What I want to test is whether there is a difference between timepoint one (t1) and two (t2) or not. A hypothesis could be: the average difference t1-t2 is sign. larger than zero (a one-sided test). Another hypothesis could be: the average difference is sign. different from zero, either larger or smaller (a two-sided test).

If you deal with a distribution of your data that ordinary Linear Mixed Models (LMMs) or Generalized LMMs (GLMMs) can handle you should vote for this option - but sometimes you deal with awkard data and permutation tests may the only thing to bail you out...

Bootsrap Confidence Intervals, Stratified Bootstrap

 Here's a worked example for comparing group averages with bootstrap confidence intervals and allowing for different subsample sizes by calling the strata argument within the bootstrap function.

The data (simulated) is set up analogous to an before-after impact experiment conducted on plots across 4 levels of a grouping factor ('stage'). Similarities were calculated for each composition before and after an impact and will be averaged over the grouping factor. Our hypothesis was that the levels of the grouping factor would show significantly different average similarities - that is, a higher/lower impact on composition. As plots were aggregated in different sites within the 'stages', this dependency had to be allowed for by use of the "strata" argument in the boot.ci call.

The conclusion from this simulated example would be that the averages similarities at stages C and D are significantly different from stages A and B. That is, as the similarities are higher in C and D than in A and B, impact on composition is significantly lower in C and D.

Custom Labels for Ordination Diagram

Here is how you do custom labels, hull, spider in a vegan ordination diagram:

Lattice Plots - Usage of Panel Functions - Different Axes For Panel-Rows - Alternating Axis Titles

I present code for a stacked graph with common axes only for panels of the same row and with axis titles at different sides. This admittedly took me days (because i had not much of a clue how to use lattice), but eventually I did it and maybe someone can use this for his/her own purpose:

Test Difference Between Diversity-Indices of Two Samples with Abundance Data

I adapted a permutation test from the PAST Software (Hammer & Harper, http://folk.uio.no/ohammer/past/diversity.html) that tests difference between diversity-indices of two samples with abundance data in R... See the example below:

Multivariate Repeated Measurements with adonis():

Please check the updated code in the comment by Wallace Beiroz, 26 January 2015 at 13:37!

Lately I had to figure out how to do a repeated measures (or mixed effects) analysis on multivariate (species) data. Here I share code for a computation in R with the adonis function of the vegan package. Credit goes to Gavin Simpson providing most of the important pieces of the below code in R-Help.