summary(model)$coefficients[,3]
or
summary(model)$coefficients[-1,3]
For example:
> counts <- c(18,17,15,20,10,20,25,13,12)
> outcome <- gl(3,1,9)
> treatment <- gl(3,3)
> glm.D93 <- glm(counts ~ outcome + treatment, family=poisson())
> summary(glm.D93)
Call:
glm(formula = counts ~ outcome + treatment, family = poisson())
Deviance Residuals:
1 2 3 4 5 6 7
-0.67125 0.96272 -0.16965 -0.21999 -0.95552 1.04939 0.84715
8 9
-0.09167 -0.96656
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 3.045e+00 1.709e-01 17.815 <2e-16 ***
outcome2 -4.543e-01 2.022e-01 -2.247 0.0246 *
outcome3 -2.930e-01 1.927e-01 -1.520 0.1285
treatment2 8.717e-16 2.000e-01 4.36e-15 1.0000
treatment3 4.557e-16 2.000e-01 2.28e-15 1.0000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05
'.' 0.1 ' ' 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 10.5814 on 8 degrees of freedom
Residual deviance: 5.1291 on 4 degrees of freedom
AIC: 56.761
Number of Fisher Scoring iterations: 4
> summary(glm.D93)$coefficients[,3]
(Intercept) outcome2 outcome3 treatment2 treatment3
1.781478e+01 -2.246889e+00 -1.520097e+00 4.358442e-15 2.278668e-15
> summary(glm.D93)$coefficients[-1,3]
outcome2 outcome3 treatment2 treatment3
-2.246889e+00 -1.520097e+00 4.358442e-15 2.278668e-15
Taka Matzmoto wrote:> Hello R users
> I like to extract z values for x1 and x2. I know how to extract coefficents
> using model$coef
> but I don't know how to extract z values for each of independent
variable. I
> looked around
> using names(model) but I couldn't find how to extract z values.
>
> Any help would be appreciated.
>
> Thanks
>
> TM
>
> #########################################################
>> summary(model)
>
> Call:
> glm(formula = y ~ x1+ x2, family = binomial)
>
> Deviance Residuals:
> Min 1Q Median 3Q Max
> -2.1397 -1.2357 0.6875 0.8517 1.5743
>
> Coefficients:
> Estimate Std. Error z value Pr(>|z|)
> (Intercept) -0.63930 1.13045 -0.566 0.572
> x1 0.69956 0.09459 7.396 1.40e-13 ***
> x2 1.51389 1.13212 1.337 0.181
> ---
> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05
'.' 0.1 ' ' 1
>
> (Dispersion parameter for binomial family taken to be 1)
>
> Null deviance: 1214.9 on 999 degrees of freedom
> Residual deviance: 1149.8 on 997 degrees of freedom
> AIC: 1155.8
>
> Number of Fisher Scoring iterations: 4
> ############################################################
>
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>
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