I need to better understand the output from netlogit in the sna package in R. Below you find an example posted online (https://rpubs.com/pjmurphy/338798), which provide a basis for my questions:
The results provide two Pseudo-R^2 Measures, (Dn-Dr)/(Dn-Dr+dfn): 0.4250345 and (Dn-Dr)/Dn: 0.5332452. Which are these? What's the difference? How do I interpret them? Is one better to use than the other?
What is Total Fraction Correct: 0.875? How do I interpret it?
nlog<-netlogit(Padgett_Business, list(Padgett_Marriage, Padgett_Party),reps=1000)
summary(nlog)
## Network Logit Model
##
## Coefficients:
## Estimate Exp(b) Pr(<=b) Pr(>=b) Pr(>=|b|)
## (intercept) -2.57893819 0.0758545 0.000 1.000 0.000
## x1 2.17792200 8.8279428 0.999 0.001 0.001
## x2 -0.02228475 0.9779617 0.517 0.483 0.972
##
## Goodness of Fit Statistics:
##
## Null deviance: 332.7106 on 240 degrees of freedom
## Residual deviance: 155.2943 on 237 degrees of freedom
## Chi-Squared test of fit improvement:
## 177.4164 on 3 degrees of freedom, p-value 0
## AIC: 161.2943 BIC: 171.7362
## Pseudo-R^2 Measures:
## (Dn-Dr)/(Dn-Dr+dfn): 0.4250345
## (Dn-Dr)/Dn: 0.5332452
## Contingency Table (predicted (rows) x actual (cols)):
##
## 0 1
## 0 210 30
## 1 0 0
##
## Total Fraction Correct: 0.875
## Fraction Predicted 1s Correct: NaN
## Fraction Predicted 0s Correct: 0.875
## False Negative Rate: 1
## False Positive Rate: 0
##
## Test Diagnostics:
##
## Null Hypothesis: qap
## Replications: 1000
## Distribution Summary:
##
## (intercept) x1 x2
## Min -7.240807 -2.540211 -2.995598
## 1stQ -6.537942 -0.820302 -1.010798
## Median -6.266030 -0.328922 -0.103392
## Mean -6.230127 0.049667 -0.006711
## 3rdQ -5.947601 0.813030 0.899497
## Max -4.705737 5.194956 4.716553