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
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,
> I have spatial data which contain
> number of landslide presence cells with respect to landslide predictors
> number of landslide absence cells with respect to same predictors.
> predictors are essentially categorical data.
> I tried logistic regression. But because of providing interaction
> 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
> The views and opinions expressed in this e-mail message are the sender's
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> Earthquake Research Dept.
> of General Directorate of Disaster Affairs.
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