[R] cross-validation / sensitivity anaylsis for logistic regression model
Dylan Beaudette
dylan.beaudette at gmail.com
Tue May 15 01:38:21 CEST 2007
Hi,
I have developed a logistic regression model in the form of (factor_1~ numeric
+ factor_2) and would like to perform a cross-validation or some similar
form of sensitivity analysis on this model.
using cv.glm() from the boot package:
# dataframe from which model was built in 'z'
# model is called 'm_geo.lrm'
# as suggested in the man page for a binomial model:
cost <- function(r, pi=0) mean(abs(r-pi)>0.5)
cv.10.err <- cv.glm(z, m_geo.lrm, cost, K=10)$delta
I get the following:
cv.10.err
1 1
0.275 0.281
Am I correct in interpreting that this is the mean estimated error percentage
for this specified model, after 10 runs of the cross-validation?
any tips on understanding the output from cv.glm() would be greatly
appreciated. I am mostly looking to perform a sensitivity analysis with this
model and dataset - perhaps there are other methods?
thanks
--
Dylan Beaudette
Soils and Biogeochemistry Graduate Group
University of California at Davis
530.754.7341
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