I'd like to do something analogous to a call to predict() with the newdata argument targeting my Amelia object.
Hi @compliancedivis. Does using
setx with fitted values not work, e.g. http://docs.zeligproject.org/articles/using_Zelig_with_Amelia.html
In the meantime I have another question. I can't seem to get log-odds output from summary() with the log-odds switch set to TRUE, and I know my model is logit (I've done it two ways -- once with a call to zlogit and once with a model= argument setting)
I'm having an issue with relogit in R. The package documentation says you can have a range of taus but I keep getting an error: "zelig(y1~x1, data = d, model = "relogit", tau = c(0.01,0.1))
Error in relogit(formula = cbind(y1, 1 - y1) ~ x1, tau = c(0.01, 0.1), : tau must be a vector of length less than or equal to 1. For multiple taus, estimate models individually." Anyone know what to do?
Error in relogit(formula = cbind(y1, 1 - y1) ~ x1, tau = c(0.01, 0.1), : tau must be a vector of length less than or equal to 1. For multiple taus, estimate models individually." Anyone know what to do?
Good evening. I would like to estimate a multinomial logit model with individual AND alternative specific variables using Zelig. I want to predict vote choice (5 parties) with previous vote choice ( alternative specific ) and economic perceptions (same value for each choice). So far i could run a mlogit model with individual specific variables but can not figure out how to include the alternative specific ones and then estimate predicted probabilities for different values of the independent variables. Thank you!
z.out <- zelig(inscat1 ~ as.factor(ed) + as.factor(racethn) +
- as.factor(income2) + as.factor(sex) + as.factor(state) +
- as.factor(date) + as.factor(empl2) + age2 +
- republican + fed, data = mergeddata, model = "mlogit", cite = F)
Error in vglm.fitter(x = x, y = y, w = w, offset = offset, Xm2 = Xm2, :
vglm() only handles full-rank models (currently)
does anyone knows what this error mean?
@skostiaev it means roughly that your model is too complex given the data available to estimate it. You can see exactly what conditions lead to this error in the VGAM source code at https://github.com/cran/VGAM/blob/master/R/vglm.fit.q
please give codes that actually run.
I don't want screenshots; I want code that I can run and see what happens. I can guess that your model is just not supported by the VGAM package, and that there is nothing to be done about that from the Zelig side. I'm willing to do some work to check if this guess is correct, but only if you set up a reproducible example demonstrating your issue. If you ar not familiar with the concept of a reproducible example you may wish to refer to https://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example
@izahn this code worked... i just wanted to do it zelig as well because zelig gives nice option to bootstrap confidence intervals.
@izahn zelig does allow to do multinomial logit, right?
Yes, zelig does multinomial logit, but it uses the
VGAM package instead of nnet.
Hi There! I'm new to Zelig but enjoying it so far. I'm trying to run an ls regression after propensity score matching using 'MatchIt ' with multiply imputed data. I know Zelig does great with post-MatchIt and does a good job with multiple MI datasets.
I've run 'MatchIt' on each of my 5 imputed datasets and saved the data as matchgen1-matchgen5 then combined them using
'matchgen.mi <- to_zelig_mi(matchgen1,matchgen2,matchgen3,matchgen4,matchgen5)', but the Zelig regression does not support weights to integrate the propensity score. Any ideas?
Thanks for your help!
Thanks for your help!