Zelig August 2013

zelig@lists.gking.harvard.edu

13 participants
12 discussions

by Sylvia Geng

Hi experts, I need some help about plotting the confidence interval. I came across your R package for plotting vertical CI online (http://rss.acs.unt.edu/Rdoc/library/Zelig/html/plot.ci.html) and wondering how exactly I can use it. My data looks like this: prof_id payment 1588646061 25262.410 1083680078 25792.190 1588646061 20282.290 1104864495 35295.120 1407837651 27368.600 1912988189 21955.710 1063400349 20268.550 1407837651 26000.370 1831176718 18945.300 1831176718 14095.950 ...... I am interested in plotting some plots like this: [cid:image001.png@01CEA56E.F7FEF570] Where the yellow dots are the payment means for each prof_id (with lowest to highest) and the vertical bars are the confidence intervals for each mean. Red line is the overall payment mean and the blue dot is the one with largest number of cases (the CI would be the narrowest). Would you please give me some insights about how I can plot such graphs with either the package above or any other methods? Thanks a lot! It would be very helpful. Thanks again, Sylvia The information contained in this transmission is proprietary to ArborMetrix, Inc. and/ or its Customers or affiliates and is intended for use only by the individual or entity to which it is addressed, and may contain information that is privileged, confidential or exempt from disclosure under applicable law. If you are not the intended recipient or it appears that this mail has been forwarded to you without proper authority, you are notified that any review, distribution, or duplication of this communication in any manner is strictly prohibited. In such cases, please contact the sender or info(a)arbormetrix.com by reply email and delete this mail from your records.

10 years, 8 months

Re: MatchIt Zelig and multiple imputation

by Kosuke Imai

Unfortunately, I don't think we have an automated procedure for everything. You would have to multiply impute the data, do matching on each imputed data set, and then combine it in zelig() using mi() function. But this does not require any programming. You can simply run the same matching procedure on each data set via matchit() and then feed the resulting multiple matched data sets into zelig(). Good luck, Kosuke Department of Politics Princeton University http://imai.princeton.edu On Sep 13, 2011, at 6:02 PM, Pingaul jb wrote: > Dear Professor, > I’m a post-doctoral student at Montreal University. I’m actually in Columbia, working and propensity scores with a colleague and using MatchIt and Zelig. First, congratulations for your packages that are very flexible. > > My question is about multiple imputation and propensity scores with these softwares. From what I understand, combining both approaches would include: > > 1/ Doing multiple imputation and testing which variables to include. > > 2/ Propensity score analysis on each imputed data set and pooling the overall balance to check if it is ok (or on each data set?). > > 3/ Calculation of the quantities of interest for each data set > > 4/ Pooling the quantities across data sets. > > I would like to know if there is a written syntax to perform the MatchIt analysis for all of the imputed data set without having to do it manually and check the overall balance. Also, in theory, the number of individuals retained after propensity score matching and the weights can be different for each imputed data set. So that we have to perform the final analysis on each one and then pool the data with a specific procedure to take into account the eventual varying Ns? I normally use Mice package for multiple imputation but it seems that Zelig handle Amelia. My colleague seems to do be able to do all that in stata, but I’m not sure how to make all the three R packages work together. > > I would be very happy if you could indicate to me a reference or a place where I can find the syntax to do that (I’ve been using R for some times so I can use packages easily but I have no programming skills). > > > Best Regards! > > > > Jean-Baptiste > - Zelig Mailing List, served by Harvard-MIT Data Center Send messages: zelig(a)lists.gking.harvard.edu [un]subscribe Options: http://lists.gking.harvard.edu/?info=zelig Zelig program information: http://gking.harvard.edu/zelig/

10 years, 8 months

Problems with gamma.mixed in Zelig

by Lester, Susan (Health)

Hi, I'm using R 3.0.1, Zelig 4.1-3 and ZeligMultilevel 0.7-0 The model in the gamma.mixed demo gives false convergence: library(ZeligMultilevel) data(coalition2) z.out <- zelig( duration ~ invest + fract + polar + numst2 + crisis + tag(1 | country), data = coalition2, model = "gamma.mixed", family = Gamma(link="log") ) WARNING: Warning in mer_finalize(ans) : false convergence (8) If I refit the model without any predictors, then it converges, but with pretty silly Std.Dev/Std.Error estimates - so this would seem to be where the problem lies: Generalized linear mixed model fit by the Laplace approximation Formula: duration ~ 1 + tag(1 | country) Data: coalition2 AIC BIC logLik deviance -1242560 -1242549 621283 -1242566 Random effects: Groups Name Variance Std.Dev. country (Intercept) 1.3621e+92 1.1671e+46 Residual 7.0281e+97 8.3833e+48 Number of obs: 304, groups: country, 14 Fixed effects: Estimate Std. Error t value (Intercept) 1.127e+02 4.808e+47 0

10 years, 8 months

Zelig Core Reference Manual

by Edward Downie

When trying to access the Zelig Core Reference Manual, I get: "The URL might be incorrect or have changed. Please go back to the homepage."

10 years, 8 months

Re: [zelig] how zelig runs simulation

by Ceylan, Hasan

My df is mydata: DATE Tot VOLUME 1 2013-05-01 08:00:00 41.19 17447212 2 2013-05-01 09:00:00 48.04 22345495 3 2013-05-01 10:00:00 58.76 24855225 4 2013-05-01 11:00:00 58.92 24756301 5 2013-05-01 12:00:00 63.96 23329007 6 2013-05-02 08:00:00 39.20 15601614 I understand this part, building a linear mode and getting the formula y=a+bx z.out <- zelig(y~s(x),data=mydata,model="ls") I also undersntand this part, given the linear model formula and explanatory variable, what would be my dependent variable. Straight forward: x.out <- setx(z.out, VOLUME=20000000) I read the documentation about how sim works but I really did not get it. As I understand simulation, it picks random numbers from a sample size. But in this case there is only one number (x.out). I really need to understand how simulation works in Zelig. Can you explain this to me? s.out <- sim(z.out,x.out) This communication is for informational purposes only. It is not intended as an offer or solicitation for the purchase or sale of any financial instrument or as an official confirmation of any transaction. All market prices, data and other information are not warranted as to completeness or accuracy and are subject to change without notice. Any comments or statements made herein do not necessarily reflect those of JPMorgan Chase & Co., its subsidiaries and affiliates. This transmission may contain information that is proprietary, privileged, confidential and/or exempt from disclosure under applicable law. If you are not the intended recipient, you are hereby notified that any disclosure, copying, distribution, or use of the information contained herein (including any reliance thereon) is STRICTLY PROHIBITED. Although this transmission and any attachments are believed to be free of any virus or other defect that might affect any computer system into which it is received and opened, it is the responsibility of the recipient to ensure that it is virus free and no responsibility is accepted by JPMorgan Chase & Co., its subsidiaries and affiliates, as applicable, for any loss or damage arising in any way from its use. If you received this transmission in error, please immediately contact the sender and destroy the material in its entirety, whether in electronic or hard copy format. Thank you. Please refer to http://www.jpmorgan.com/pages/disclosures for disclosures relating to European legal entities.

10 years, 8 months

plot.ci() still not working for me

by Gabi Huiber

I am trying to run the example from the plot.ci documentation here -- http://rss.acs.unt.edu/Rdoc/library/Zelig/html/plot.ci.html. Unfortunately, even changing the plot.ci() call to include the var statement as Matt Owen explained back in January still won't work. I tried this: data(turnout) z.out <- zelig(vote ~ race + educate + age + I(age^2) + income, model = "logit", data = turnout) age.range <- 18:95 x.low <- setx(z.out, educate = 12, age = age.range) x.high <- setx(z.out, educate = 16, age = age.range) s.out <- sim(z.out, x = x.low, x1 = x.high) plot.ci(s.out, *var=turnout$age*, xlab = "Age in Years", ylab = "Predicted Probability of Voting", main = "Effect of Education and Age on Voting Behavior") legend(45, 0.52, legend = c("College Education (16 years)", "High School Education (12 years)"), col = c("blue","red"), lty = c("solid")) I got this: Error in xmatrix[, position] : subscript out of bounds In addition, demo(vertci) seems to be disabled as well. Thank you, Gabi Huiber

10 years, 8 months

handling of factors when using 2SLS: setx() and sim() report "subscript out of bounds" errors

by John G. Bullock

Hello, I've recently run across a series of problems when I try to estimate models that include factors via 2SLS. The problems arise in versions 3.5.5 and 4.1.3. (I'm also using I'm using systemfit 1.1.14.) In all cases, zelig() works fine, but problems arise with setx() or sim(). Here is a minimal example: data(klein) klein$fac <- factor(rep(letters[1:3], times = 7)) z.out <- zelig( formula = list( "mu1" = Wtot ~ fac + P1, "mu2" = fac ~ X + X1 + P1, "inst" = ~ X + X1 + P1), model = "twosls", data = klein) x.out <- setx(z.out, fac = 'b') s.out <- sim(z.out, x = x.out) In Zelig 4.1.3, the setx() command above yields an "Error in form[[3]] : subscript out of bounds" message. In Zelig 3.5.5, there is no problem with setx(), but the sim() command yields: "Error: subscript out of bounds." If I make numeric dummies out of the factor, the problem vanishes in both versions of Zelig: klein$b <- as.numeric(klein$fac == 'b') klein$c <- as.numeric(klein$fac == 'c') z.out <- zelig( formula = list( "mu1" = Wtot ~ b + c + P1, "mu2" = b ~ X + X1 + P1, "mu3" = c ~ X + X1 + P1, "inst" = ~ X + X1 + P1), model = "twosls", data = klein) x.out <- setx(z.out, b = 0) s.out <- sim(z.out, x = x.out) But when a factor has many levels, it can be laborious to convert it into a set of dummies that will work with setx() and sim(). (Using model.matrix() doesn't help here: it creates matrices of dummies, and sim() doesn't seem to like matrices in formulas.) Short of dummying out my factors, is there anything that I can do to use setx() and sim() when my model has factors and I want to use 2SLS? Thank you, John

10 years, 8 months

Re: [zelig] Zelig Digest, Vol 123, Issue 1

by Hasan Ceylan

I have a question around running a simulation with Zelig. 1. I'm building a Zelig with la model between two variables 2. Setting one value to predict another 3 running simulation to get my predicted values Q: how does Zelig run simulation? Based on what? Can you please clarify this? Thank you, Hasan

10 years, 9 months

Does Zelig 4 fit arima models?

by Cesar Zucco

Some code I wrote under Zelig 3.X to fit an arima model no longer works. R tells me that ** The model "arima" is not available with the currently loaded packages, ** and is not an official Zelig package. ** The model's name may be a typo. Arima models are still listed on the website http://projects.iq.harvard.edu/zelig/pages/description-listing-models But they don't appear to be in any of the sub-packages. I suppose the website is outdated, right? Cesar

10 years, 9 months

method for estfun()

by Cesar Zucco

In previous versions of Zelig, it was possible to apply the function to a saved zelig object as estfun(zelig.object), where zelig.oject is the output of a probit. Now it returns: *Error in UseMethod("estfun") : no applicable method for 'estfun' applied to an object of class "c('zelig', 'probit')"* I also tried estfun(zelig.object$results), which I thought would work because $results looks a lot like the glm output (which works with estfun), but it didn´t. In this case I get: *Error: object of type 'closure' is not subsettable* Can anybody think of a workaround? Thanks, cz

10 years, 9 months

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Zelig August 2013