Access z-value and other statistics in output of Zelig relogit - r

Question

I want to compute a logit regression for rare events. I decided to use the Zelig package (relogit function) to do so.
Usually, I use stargazer to extract and save regression results. However, there seem to be compatibility issues with these two packages (Using stargazer with Zelig).
I now want to extract the following information from the Zelig relogit output:
Coefficients, z values, p values, number of observations, log likelihood, AIC
I have managed to extract the p-values and coefficients. However, I failed at the rest. But I am sure these values must be accessible somehow, because they are reported in the summary() output (however, I did not manage to store the summary output as an R object). The summary cannot be processed in the same way as a regular glm summary (https://stats.stackexchange.com/questions/176821/relogit-model-from-zelig-package-in-r-how-to-get-the-estimated-coefficients)
A reproducible example:
##Initiate package, model and data
require(Zelig)
data(mid)
z.out1 <- zelig(conflict ~ major + contig + power + maxdem + mindem + years,
data = mid, model = "relogit")
##Call summary on output (reports in console most of the needed information)
summary(z.out1)
##Storing the summary fails and only produces a useless object
summary(z.out1) -> z.out1.sum
##Some of the output I can access as follows
z.out1$get_coef() -> z.out1.coeff
z.out1$get_pvalue() -> z.out1.p
z.out1$get_se() -> z.out1.se
However, I did not find similar commands for other elements, such as z values, AIC etc. However, as they are shown in the summary() call, they should be accessible somehow.
The summary call result:
Model:
Call:
z5$zelig(formula = conflict ~ major + contig + power + maxdem +
mindem + years, data = mid)
Deviance Residuals:
Min 1Q Median 3Q Max
-3.0742 -0.4444 -0.2772 0.3295 3.1556
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) -2.535496 0.179685 -14.111 < 2e-16
major 2.432525 0.157561 15.439 < 2e-16
contig 4.121869 0.157650 26.146 < 2e-16
power 1.053351 0.217243 4.849 1.24e-06
maxdem 0.048164 0.010065 4.785 1.71e-06
mindem -0.064825 0.012802 -5.064 4.11e-07
years -0.063197 0.005705 -11.078 < 2e-16
(Dispersion parameter for binomial family taken to be 1)
Null deviance: 3979.5 on 3125 degrees of freedom
Residual deviance: 1868.5 on 3119 degrees of freedom
AIC: 1882.5
Number of Fisher Scoring iterations: 6
Next step: Use 'setx' method

Answer 1

Use from_zelig_model for deviance, AIC.
m <- from_zelig_model(z.out1)
m$aic
...
Z-values are coefficient / sd.
z.out1$get_coef()[[1]]/z.out1$get_se()[[1]]