[R] need a clarification on logistic regression

[Ahmet Temiz]

hello

I need a clarification.

in logistic regression, saturated model having all combinations and
interactions of variables should be constructed in this way ? : 

> rsat2=glm(cbind(landp,landa) ~ 
as.factor(rlito)*as.factor(rslp)*as.factor(rasp)*as.factor(rplc)*as.factor(rwi),family=
binomial(link=logit),data=rdf46)

then

using stepAIC to eliminate some models having high AIC values. 

> stpAIC_r2=stepAIC(rsat2,list(lower=~1,upper=formula(rsat2)),trace=F)

But obtained final model looks very intricate and I couldn't interpret it.

> stpAIC_r2$anova

Do I have to consider last line (13) ?


1                                                                            
      
2  -
as.factor(rlito):as.factor(rslp):as.factor(rasp):as.factor(rplc):as.factor(rwi)
3                   -
as.factor(rslp):as.factor(rasp):as.factor(rplc):as.factor(rwi)
4                  -
as.factor(rlito):as.factor(rslp):as.factor(rasp):as.factor(rwi)
5                  -
as.factor(rlito):as.factor(rslp):as.factor(rplc):as.factor(rwi)
6                                  -
as.factor(rlito):as.factor(rslp):as.factor(rwi)
7                  -
as.factor(rlito):as.factor(rasp):as.factor(rplc):as.factor(rwi)
8                                  -
as.factor(rlito):as.factor(rplc):as.factor(rwi)
9                 -
as.factor(rlito):as.factor(rslp):as.factor(rasp):as.factor(rplc)
10                                 -
as.factor(rslp):as.factor(rasp):as.factor(rplc)
11                                -
as.factor(rlito):as.factor(rslp):as.factor(rplc)
12                                -
as.factor(rlito):as.factor(rasp):as.factor(rplc)
13                                -
as.factor(rlito):as.factor(rslp):as.factor(rasp)
   Df   Deviance Resid. Df Resid. Dev      AIC
1  NA         NA       191   458.3157 3310.353
2   1  0.3148536       192   458.6305 3308.668
3  24 31.8915731       216   490.5221 3292.560
4   7  1.3523216       223   491.8744 3279.912
5  13 13.1002785       236   504.9747 3267.012
6  19 23.7270352       255   528.7017 3252.740
7   7  4.8455686       262   533.5473 3243.585
8   9  5.7980351       271   539.3453 3231.383
9   8  7.9086994       279   547.2540 3223.292
10 40 50.8028626       319   598.0569 3194.095
11 17 12.8919748       336   610.9489 3172.987
12 14  8.1175215       350   619.0664 3153.104
13 18 27.9371216       368   647.0035 3145.041



I will be appreciate if you explain.


regards

Ahmet Temiz
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