Skip to content

GLM

2 messages · Mahnaz Rabbaniha, Bob OHara

Original
Mahnaz Rabbaniha
# 
Dear all

I want to find regression between fish larva abundance and some
abiotic factor ,i used this code:

glm(formula = mychto ~ po4 + No3 + Si + Tn)


result:
Deviance Residuals:
    Min       1Q   Median       3Q      Max
-26.586  -18.262  -12.296   -2.949  226.229

Coefficients:
            Estimate Std. Error t value Pr(>|t|)
(Intercept)  67.4211    73.9781   0.911    0.371
po4          -0.2887     1.6037  -0.180    0.859
No3           0.9151     4.5261   0.202    0.841
Si           -0.1145     0.4850  -0.236    0.815
Tn           -1.1568     4.4818  -0.258    0.798

(Dispersion parameter for gaussian family taken to be 2444.917)

    Null deviance: 63156  on 29  degrees of freedom
Residual deviance: 61123  on 25  degrees of freedom
AIC: 325.72


my question is about the acceptable this AIC, or this result with
goodness of fit?

thanks
Bob OHara
#
On 03/07/2013 04:24 PM, Mahnaz Rabbaniha wrote:
AIC tells you nothing about goodness of fit, it is used to compare 
different models.

A better way to assess goodness of fit is to look at the data and the 
model. It's clear that you have very skewed data (look at the distances 
between the quartiles of the residuals), so a Gaussian model, which 
assumes the residuals are symmetric, is inappropriate. It might make 
more sense to use a Poisson distribution, although you will probably 
need to account for over-dispersion (there are a few ways of doing 
this). Also, once you've fitted a glm, you can use plot() to get some 
useful model-checking plots (e.g. residuals).

There is more advice in the links here: 
<http://r.789695.n4.nabble.com/Checking-the-assumptions-for-a-proper-GLM-model-tp1559502p1560503.html>.

Bob