[R] master thesis

[Ben Bolker]

Francesca Sorbie <fsorbie <at> hotmail.com> writes:

> 
> Hi, 
> 
> For my master thesis I have 24 micro-plots on which I 
>   did measurements during 3 months. 
> 
> The measurements were: 

 > - Rainfall and runoff events throughout 3monts 
>  (runoff being dependant on the rainfall, a coefficient (%)
> has been made per rainfall event and per 3 months)
> - Soil texture (3 different textures were differentiated)
> - Slope (3 classes of slopes)
> - Stoniness (one time measurement)
> - Random roughness (throughout 3 months)
> - Land use (crop land or grazing land)
> - Vegetation cover (throughout 3 months)
> - Vegetation height (throughout 3 months, only measured on cropland)
> - Antecedent moisture content (throughout 3 months)

> Now I would like to investigate the effect of all these variables on
> the rainfall/runoff. For example does a steeper slope have a larger
> effect on the runoff than the soil texture?  What are the
> possibilities in R?

  I'm afraid this is an R list, not a statistical consulting list.
You probably want to do multivariate linear regression with lm(), after
appropriate graphical exploration of the data to make sure there
aren't glaring nonlinearities.  You probably need to cut down
or condense your list of predictors somehow; the rule of thumb
is that with n observations you should generally not try to fit 
a model with more than n/10 parameters.
   Don't be tempted by stepwise regression.  Read Frank Harrell's
book on Regression Modeling Strategies, and (!!!) get some local
statistical help -- if you're a student, someone should be teaching
you ... 

  Ben Bolker