Dear List,

I am trying to predict the extinction risk of a species based on its life history. I will detail my method below and would welcome comments as to why the results are not as i expected.


First i fit my model -

>model1 <- glm(THREAT~ HAB*BS + FR + WO + SEA + PD, data=traits, family="binomial")

			Where THREAT is TRUE (1) / FALSE (0).

			Where BS, FR etc are factors with multiple levels.


I then predicted the probability of a species being threatened or not using

>print(predict(model1, type = "response"))

example output:- 

       1          	2          		3          		4          		5          		6          		7 
0.44659200 0.65221495 0.71357243 0.71357243 0.71357243 0.71357243 0.71357243 
       8          	9         		10         		11         		12         		13         		14 
0.71357243 0.65221495 0.65221495 0.65221495 0.65221495 0.65221495 0.65221495

I interpret this as species 1 has a 45% chance (probability) of being threatened etc....

I then wanted to see how this relates to the "true" threat level so i looked at species 1 and it was classed as threatened, which disagrees with the predict results, although marginally. In fact most of the predict results do not agree with the "real" threat level, some species have a probability of 0.17 which to me says they are non threatened but in "real" they are classed as threatened.

This is important as if these are not matching, at least most of the time, then how can i confidently predict the response of a species when i don't know its "real" response?

I hope this makes sense.

Chris






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