Zelig

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631 discussions

Fitted values from a logit.gee Zelig model

by Nils B. Weidmann

I’m trying to extract fitted values from a logit.gee model (m1), using m1$fitted.values However, this returns NULL (as does m1$coefficients and the other fields listed on p. 265 of the Zelig documentation). I know I can simply run a glm as a workaround, but nevertheless wanted to report this issue. Best Nils -- Nils B. Weidmann Professor of Political Science University of Konstanz http://cnc.uni.kn

10 years, 3 months

Rstatistics.zip

by Edward Downie

I'm unable to locate this file: Rstatistics.zip I'm told I need in: http://projects.iq.harvard.edu/rtc/r-stats to run Instructor - Ista Zahn's workshop: R Regression Models I gather Rstatistics.zip contains the NH11 data Thanks for the help! -Edward Downie

10 years, 4 months

Obtaining risk ratio from simulation output

by Chris Compton

Dear List Members, In a previous version of Zelig (unsure of version number) it was possible to extract both the first difference and risk ratio from the summary () function, as in the below steps Model: z.out.1 <- zelig(bhbahi~treatment+agecat+breedcat+herd_initials, model = "logit", data = dat) Simulated quantities of interest: x.0 <- setx(z.out.1, treatment = "Control") x.1 <- setx(z.out.1, treatment = "Treatment") s.out.2 <- sim(z.out.1, x = x.0, x1 = x.1) Summary of first difference and risk ratio summary(s.out.2) However, changes have removed risk ratio from the quantities of interest and summary () output. The $qi now contains only: > names(s.out.2$qi) [1] "Expected Values: E(Y|X)" "Expected Values: E(Y|X1)" [3] "Predicted Values: Y|X" "Predicted Values: Y|X1" [5] "First Differences: E(Y|X1) - E(Y|X)" My question is- is there a convenient way to obtain risk ratios and confidence intervals with the new version? I am running Zelig version 4.2-1 on R version 3.0.2 on a Windows 7 platform Thanks for any help. Chris Compton

10 years, 5 months

Question on: "an error fitting this statistical model."

by Vijayaraghavan, Rajesh

Dear Zelig users, Greetings! I am relatively new to Zelig and R. But have a question when I run a linear least square model: output <- zelig(y ~ x, model ="ls"). When I run using my data, I get the following warning message. In value[[3L]](cond) : There was an error fitting this statistical model. I tried to look around to see what the issue could be but didn't have much luck. I tried to see if it is a data issue and played around with lalonde to try replicating so that I could forward to you. data(lalonde) z.out <- zelig(re78 ~ treat + age + educ + black + hispan + married + re74 + re75, data = lalonde, model = "ls") output does not have any warnings. However if I add "nodegr" covariate, I get the warning message again. z.out <- zelig(re78 ~ treat + age + educ + black + hispan + nodegr + married + re74 + re75, data = lalonde, model = "ls") Any advice on what should I do to fix would be deeply appreciated. If you think it may be addressed elsewhere, please let me know. Best , Rajesh

10 years, 5 months

(no subject)

by elham haem

Hi I have a data set with 256 infants. only 10 out of 256 were low birth weight(y bar=10/256). I want to evaluate low birth weight risk factors by relogit model. when I run my code I receive an error. I have attached my data set and my code. please help me to fit this model. Thanks in advance. Elham

10 years, 5 months

2 Errors: No log-link for Gamma Regressions and Setx not working

by Rogério Barbosa

Hi, I'm facing two difficulties... *The first one:* I'm trying to estimate a survey weighted Gamma Regression with log link, but I found out that Zelig inform just the results for the inverse link. Adding "family=Gamma(link=log)" does not work. See the example below: install.packages("Zelig") require(Zelig) #Loading data data(api, package = "survey") # Gamma inverse z.inverse <- zelig(api00 ~ meals + yr.rnd + as.factor(awards), model = "gamma.survey", weights = ~pw, data = apistrat, family=Gamma(link=inverse)) # Gamma log z.log <- zelig(api00 ~ meals + yr.rnd + as.factor(awards), model = "gamma.survey", weights = ~pw, data = apistrat, family=Gamma(link=log)) #comparison coefficients(z.inverse) == coefficients(z.log) *#inverse-link and log-link coefficients must be different, but they are not* * (Intercept) meals yr.rndYes as.factor(awards)Yes * * TRUE TRUE TRUE TRUE * ######################### g.inverse <- glm(api00 ~ meals + yr.rnd + as.factor(awards), weights = pw, data = apistrat, family=Gamma(link="inverse")) g.log <- glm(api00 ~ meals + yr.rnd + as.factor(awards), weights = pw, data = apistrat, family=Gamma(link="log")) #comparison coefficients(g.inverse) == coefficients(g.log) *#glm brings the correct results* * (Intercept) meals yr.rndYes as.factor(awards)Yes * * FALSE FALSE FALSE FALSE * *The second one:* I'm not getting the output for setx in any model! Not even for "model='ls' " # In the example above: meals_seq=seq(from=1,to=30,by=1) setx(z.inverse, meals=meals_seq) *Call:* *NULL* *Model name = * *Formula = NULL* *Complete data.frame:* *NULL* *Model Matrix (Design Matrix):* *NULL* I'm using R 3.0.2 and Zelig 4.2-1. Rolling back to Zelig 3.5.4 is not worth in this case... setx works fine in that version, but "gamma.survey" does not. thanks in advance, Rogério J Barbosa Universidade de São Paulo, Brazil

10 years, 5 months

Re: [zelig] zelig/twosls

by Kosuke Imai

Yes, you need an instrument (or something else)! Best, Kosuke --------------------------------------------------------- Kosuke Imai Office: Corwin Hall 036 Professor Phone: 609-258-6601 Department of Politics Fax: 609-258-1110 Princeton University Email: kimai(a)Princeton.Edu Princeton, NJ 08544-1012 http://imai.princeton.edu --------------------------------------------------------- On Nov 11, 2013, at 5:39 PM, aschmid1 <aschmid1(a)stevens.edu> wrote: > Dear Dr. Imai, > I'll greatly appreciate your advice. I'm trying to use twosls for VAR2 that has only lags but no exogenous variables: > y1(t)=a01*y2(t) + a11*y1(t-1) + a12*y1(t-2) + a12*y1(t-1) + a22*y1(t-2) > y2(t)=b01*y1(t) + b11*y1(t-1) + b21*y1(t-2) + b12*y2(t-1) + b22*y2(t-2) > > Do I have to specify instrumental variables for this model? > > Thanks much, Alec Schmidt

10 years, 6 months

summary() does not work with mixed models and multiply imputed data sets

by Mattia Guidi

Hello, I am running several regressions with multiply imputed data sets, and Zelig is unable to provide the summary of the regression results when I run a multilevel model (this happens with any multilevel model supported by ZeligMultilevel). A reproducible example is the following: *require(Amelia)* *require(Zelig)* *require(ZeligMultilevel)* *data(freetrade)* *amelia.ft <- amelia(freetrade, ts="year", cs="country")* *# Non-multilevel model* *z.out1 <- zelig(tariff ~ pop + country, data=amelia.ft, model="ls")* *# summary() works fine* *summary(z.out1)* *# Multilevel model* *z.out2 <- zelig(tariff ~ pop + tag(1 | country), data=amelia.ft, * * model="ls.mixed")* *# summary() does not work* *summary(z.out2)* The error message is: *Error in object[[1]]$result$call : $ operator not defined for this S4 class* The same issue is described here<http://stackoverflow.com/questions/16571580/multi-level-regression-model-on…>, where a solution is also provided in the form of a slightly modified version of summary.MI(). The problem is that once the modified version of summary.MI() has been loaded, the function no longer works with standard models. Is there a better workaround? Thank you in advance, Mattia -- Mattia Guidi, Ph.D Post-doctoral Fellow LUISS Guido Carli Department of Political Science & School of Government Via di Villa Emiliani 14 00197 Rome (Italy) Tel: +39 06 8522 5706

10 years, 6 months

need to extract the qi values

by Mike Dylan

hi, I need to extract qi values from s.out to bring the results to another app. When I do this s.out$qi, I get all null values. Any idea what might be wrong? Regards, Sean

10 years, 6 months

Zelig simulation

by Mike Dylan

Zelig package is what I have been looking for a long time. I slight problem is that I dont understand how sim() is run. I read through the docs and I think it is written for graduate students. We can run the numbers but at the end we need to be able to explain the results to the audience. Can somebody explain with an example, how does sim() work? "Zelig simulates parameters from classical *maximum likelihood* models using asymptotic normal approximation to the log-likelihood. This is the same assumption as used for frequentist hypothesis testing (which is of course equivalent to the asymptotic approximation of a Bayesian posterior with improper uniform priors). See King, Tomz, and Wittenberg (2000)<http://gking.harvard.edu/files/abs/making-abs.shtml>. For *Bayesian models*, Zelig simulates quantities of interest from the posterior density, whenever possible. For *robust Bayesian models*, simulations are drawn from the identified class of Bayesian posteriors." Regards, Mike

10 years, 6 months

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