[R] log-linear

Spencer Graves spencer.graves at pdf.com
Mon Apr 7 16:25:07 CEST 2003


	  1.  What did you use for logistic regression?  "glm"?  If your 
response variable is "number of landslides", I would think that "glm" 
with "family = poisson" might be appropriate.  Have you checked the R 
help for "?glm" and "?family" and the R search site at 
"http://www.r-project.org/" -> search -> "R search site"?  In 
particular, if you don't have "Modern Applied Statistics with S" by 
Venables and Ripley (2002), I suggest you get a copy.  This is the best 
reference I know on R.  If you've digested Venables and Ripley, at least 
on "glm", the next best book I know for your issues may be  McCullagh P. 
and Nelder, J. A. (1989) Generalized Linear Models (London: Chapman and 
Hall).

	  2.  You can use interactions with logistic regression, as you could 
with Poisson regression, "glm(..., family = poisson)".  If your 
explanatory variables are all categorical, then you might have a problem 
with estimating too many parameters:  If you have 5 categories in one 
variable and 7 in another, the main effects will estimate 4=(5-1) and 
6=(7-1) parameters, and the interaction will involve 4*6 = 24 
parameters.  Moreover, if you do NOT have data on at least 24 
sufficiently different combinations out of the 5*7 = 35 possible, you 
won't be able to estimate all the parameters in the interaction.  I 
suggest you try to construct at least ordinal scales, code the 
categories as numbers whereever that might be done plausibly, then look 
for linear terms, parabolics, etc., and linear*linear interactions, 
etc., THEN look for large residuals from the fitted model.

Hope this helps,
Spencer Graves

orkun wrote:
> hello
> 
> I have spatial data which contain
>  number of landslide presence cells with respect to landslide predictors 
> and
>  number of landslide absence cells with respect to same predictors.
> 
> predictors are essentially categorical data.
> 
> I tried logistic regression. But because of providing interaction 
> capability
> of predictors, I want to use log-linear method.
> I hesitate the way I should use landslide count as response variable.
> only landslide presence data should be regarded ? or both landslide 
> presence and absent data should be regarded as response variable ?
> 
> I will appreciate if anyone can supply information
> 
> thanks in advance
> 
> Ahmet Temiz
> Gen Dir of Disaster of Affairs
> 
> TURKEY
> 
> 
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