Dear All,

I 
am trying to analyze the effect of a warming treatment on plant growth. 
The warming treatment is associated with some drying of the soil, and I 
would like to determine if/how much of the growth response is due to 
drying. My original idea was to include soil moisture as a covariable in
 the model (which would include all variation from plot to plot, 
including that due to the warming treatment) and see how this changed 
the warming effect. However, I recently looked at Gelman and Hill 
(2007), where they explain in chapter 9 that including post-treatment 
variables is highly problematic. I would greatly appreciate any 
suggestions (or references) for a more appropriate way to distinguish 
between direct effects of warming and indirect effects due to reduced 
soil moisture.

original model format:
model <- lm(growth ~ cov + warming, data = x)

(probably incorrect) model with soil moisture added as covariable:
model <- lm(growth ~ cov + soilmoisture + warming, data = x)

variables:
growth = response variable (annual shoot length measured in x individual plots)
cov = pre-warming covariable (annual shoot length in years before warming)
soilmoisture = soil moisture measured in each individual plot (continuous variable, measured during years with warming)
warming = categorical variable (warmed or unwarmed)

Thank you in advance for your help!
Melissa

----
Melissa Dawes, PhD
Research Group Alpine Ecosystems
WSL Institute for Snow and Avalanche Research SLF
Flüelastrasse 11
7260 Davos Dorf
Switzerland


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