[R] Chi square value of anova(binomialglmnull, binomglmmod, test="Chisq")

[lincoln]

So sorry,

My response variable is "site" (not "gender"!).
The selection process was:

> str(data)
'data.frame':	1003 obs. of  5 variables:
 $ site  : Factor w/ 2 levels "0","1": 1 1 1 1 1 1 1 1 1 1 ...
 $ sex   : Factor w/ 2 levels "0","1": NA NA NA NA 1 NA NA NA NA NA ...
 $ age   : Factor w/ 2 levels "0","1": 1 1 1 1 1 1 1 1 1 1 ...
 $ cohort: Factor w/ 10 levels "1999","2000",..: 10 10 10 10 10 10 10 10 10
10 ...
 $ birth : Factor w/ 3 levels "5","6","7": 3 3 2 2 2 2 2 2 2 2 ...
> datasex<-subset(data, sex !="NA")

*Here below the structure of the analysis and only the anova.glm of the
last, selected model, mod4:
*
>mod1 <- glm(site ~ sex + birth + cohort + sex:birth, data=datasex, family =
binomial)
>summary(mod1)
>anova(mod1,update(mod1,~.-sex:birth),test="Chisq")

>mod2 <- glm(site ~ sex + birth + cohort, data=datasex, family = binomial)
>summary(mod2)
>anova(mod2,update(mod2,~.-sex),test="Chisq")

>mod3 <- glm(site ~ birth + cohort, data=data, family = binomial)
>summary(mod3)
>anova(mod3,update(mod3,~.-birth),test="Chisq")

>mod4 <- glm(site ~ cohort, data=data, family = binomial)
>summary(mod4)
>anova(mod4,update(mod4,~.-cohort),test="Chisq")
Analysis of Deviance Table

Model 1: site ~ cohort
Model 2: site ~ 1
  Resid. Df Resid. Dev Df Deviance P(>|Chi|)    
1       993     1283.7                          
2      1002     1368.2 -9  -84.554 2.002e-14 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 

*My question:*
In this case, the Chi2 value would be the difference in deviance between
models and d.f. the difference in d.f. (84.554 and 9)?
In other words may I correctly assess: /"cohorts were unevenly distributed
between sites ( Chi2=84.5, df=9, p < 0.001)"/?



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