I would first check whether z.out has what you want. To do this, you can
do summary(z.out). Then, I would also check whether quantile(Estdata$q30,
prob = 0.25) and quantile(Estdata$q30, prob = 0.75) are returning
appropriate numbers by just typing those commands at R prompt. If they
are, you can send up traceback().
Kosuke
On Sat, 24 Feb 2007, Kirill Kalinin wrote:
> Dear Kosuke,
>
> I appreciate your help on my matters very much!
>
> 1. I managed to calculate p-values, by using mean(s.out$fd > 0) (as far as I
> see it now: if mean()=1 then p-value will be around 0.001, and if mean()=95
> then p-value is around 0.05).
>
> 2. I ran into the problem when was making split file, so as to run several
> equations at the same time. I wanted to split calculations with Q61. Am I
> doing something wrong?
>
> z.out <- zelig(putin ~ age + q15, weights=WEIGHT$ttt, data = ttt, model =
> "logit", by=Q61)
>
> 3. I am also trying to get quartiles from 'Income' variable in a following
> way:
>
> x.high <- setx(z.out, q30=quantile(Estdata$q30, prob = 0.25))
> x.low <- setx(z.out, q30=quantile(Estdata$q30, prob = 0.75))
>
> But I am getting a warning message instead:
> is.na() applied to non-(list or vector) in: is.na(x)
>
> Could you tell me what the problem with this might be?
>
> Thank you a lot for your help!
>
> All the best,
> Kirill
> -----------------------------------
> Dear Kosuke,
>
> I appreciate your help on my matters very much!
>
> 1. I managed to calculate p-values, by using mean(s.out$fd > 0) (as far as I
> see it now: if mean()=1 then p-value will be around 0.001, and if mean()=95
> then p-value is around 0.05).
>
> 2. I ran into the problem when was making split file, so as to run several
> equations at the same time. I wanted to split calculations with Q61. Am I
> doing something wrong?
>
> z.out <- zelig(putin ~ age + q15, weights=WEIGHT$ttt, data = ttt, model =
> "logit", by=Q61)
>
> 3. I am also trying to get quartiles from 'Income' variable in following
> way:
>
> x.high <- setx(z.out, q30=quantile(Estdata$q30, prob = 0.25))
> x.low <- setx(z.out, q30=quantile(Estdata$q30, prob = 0.75))
>
> But I am getting a warning message instead:
> is.na() applied to non-(list or vector) in: is.na(x)
>
> Could you tell me what the problem with this might be?
>
> Thank you a lot for your help!
>
> All the best,
> Kirill
>
>
>
>
>
>
>
>
>
>
>
>
> yes, it's the usual confidence interval on the quantity of interest and so
> your interpretation is correct. There is no option, currently, in sim()
> that lets you calculate the p-values, but you can do it by hand. For
> example, you can do mean(s.out$fd > 0) to calculate the proportion of
> simulation draws that are greater than 0.
>
> Kosuke
>
> On Fri, 23 Feb 2007, Kirill Kalinin wrote:
>
>> Dear Kosuke,
>>
>> Thank you a lot for your prompt reply! It's great that I can use it to
> work
>> with the percentages. I wonder if the confidence interval which I got in
> the
>> output below can be interpreted as usual, so that the null hypothesis
> can't
>> be rejected at 0.05 level, is this correct? Also I wonder is there an
>> option in sim() to get confidence intervals together with p-values, so as
> it
>> could be easier to deal with the 'first differences' signficance.
>>
>> ----------------Output----------------------------
>> First Differences in Expected Values: E(Y|X1)-E(Y|X)
>> mean sd 2.5% 97.5%
>> 1 0.00973 0.01058 -0.01066 0.03029
>> --------------------------------------------------
>> Thank you a lot for your help!
>>
>> All the best,
>> Kirill
>>
>>
>>
>> ----------------------------------------
>>> Thank you very much for you help on my matter. Actually, I need to
>>> calculate the difference in the predicted probabilities of Russian
>>> voters choosing Putin when explanatory variable shifts from its minimum
>>> to its maximum value, holding other terms in the equation constant at
>>> their medians. I am trying to get everything right: could you tell me
>>> what 'Mean' in first differences stand for?
>>
>> Zelig simulates the quantities of interest and so "Mean" is the mean of
>> this simulated quantitites (the default is 1000 simulations). You can
>> think of it as a point estimate of the quantity of interest.
>>
>>> Another important question is: if I have 10 variables, for example, and
>>> calculate first differences, holding the rest at their medians, will all
>>> 'first differences' sum up to "0" and predicted probabilities to "1"? If
>>> so, it could help me to claim that, say, the value of 0.15 in first
>>> differences between young and old would give Putin 15% of the vote! If
>>> not so, is it hard to make it Zelig? In fact, I am trying to follow T.
>>> Colton's approach in "Transitional citizens" (2000), so as I could
>>> compare my calculations with his as well. And, finally do you know about
>>> any book for beginners to help to understand simulation techniques with
>>> Zelig? It's a new promising field for me!
>>
>> Yes, your interpretation is correct. The first differences should sum up
>> to and the predicted probabilities sum up to 1 in the case of the
>> logit/probit if that's what you are using.
>>
>> Kosuke
>>
>>>
>>> All the best,
>>> Kirill
>>>
>>> -------------------------------------------------
>>> it's already on our website - it will take a few days for it to appear at
>
>>> CRAN. Try:
>>>
>>> install.packages("Zelig", repos = "http://gking.harvard.edu")
>>>
>>> Kosuke
>>>
>>> -----------------------------------------------------
>>> Kosuke Imai Office: Corwin Hall 041
>>> Assistant Professor Phone: 609-258-6601
>>> Department of Politics eFax: 973-556-1929
>>> Princeton University Email: kimai(a)Princeton.Edu
>>> Princeton, NJ 08544-1012 http://imai.princeton.edu
>>> -----------------------------------------------------
>>>
>>> On Wed, 21 Feb 2007, Kirill Kalinin wrote:
>>>
>>>> Dear Kosuke,
>>>>
>>>> Thank you for your help! I'll be downloading a new version from
>>>> www.r-project.org later today.
>>>>
>>>> All the best,
>>>> Kirill
>>>>
>>>>
>>>>
>>>>
>>>> Dear Kirill,
>>>>
>>>> Thanks for the bug report. We've fixed this problem and will
>>>> release a new version later today.
>>>>
>>>> Many thanks,
>>>> Kosuke
>>>>
>>>> ---------------------------------------------------------
>>>> Kosuke Imai Office: Corwin Hall 041
>>>> Assistant Professor Phone: 609-258-6601
>>>> Department of Politics Fax: 973-556-1929
>>>> Princeton University Email: kimai(a)Princeton.Edu
>>>> Princeton, NJ 08544-1012 http://imai.princeton.edu
>>>> ---------------------------------------------------------
>>>>
>>>>
>>>>
>>>> On Feb 20, 2007, at 9:03 AM, Kirill Kalinin wrote:
>>>>
>>>>> Dear Kosuke,
>>>>>
>>>>> Olivia advised me to address my problem to you, which is when I am
>>>>> trying to
>>>>> run setx() with the ordered catagorical variables (metric variables
>>>>> work
>>>>> fine) in 'logit' model I get "Error: protect(): protection stack
>>>>> overflow".
>>>>> What might be the solution to the problem?
>>>>>
>>>>> Thank you a lot for your help!
>>>>>
>>>>> Best regards,
>>>>> Kirill
>>>>>
>>>>> --------------------------------------
>>>>>
>>>>>
>>>>>> Dear Olivia,
>>>>>>
>>>>>> Thank you a lot for your prompt and detailed reply! Well, I
>>>>>> changed the
>>>>>> script as you advised to, but it doesn't seem to help to resolve the
>>>>>> issue. Same error appears when I am trying to run setx(). Are there
>>>>>> any other suggestions of what might be wrong with the script?
>>>>>>
>>>>>> Here is what I'm getting on my console now:
>>>>>>
>>>>>>> q15<- as.ordered(Q15)
>>>>>>> age<-as.ordered(AGE)
>>>>>>> ttt<-data.frame(q15=q15,age=age, putin=PUTIN_BI)
>>>>>>> z.out <- zelig(putin ~ age + q15, data = ttt, model = "logit")
>>>>>>> x.low <- setx(z.out, age = 1)
>>>>>> Error: protect(): protection stack overflow
>>>>>>> x.high <- setx(z.out, age = 4)
>>>>>> Error: protect(): protection stack overflow
>>>>>>
>>>>>> Thank you a lot for you help!
>>>>>> Best wishes,
>>>>>> Kirill
>>>>>>
>>>>>>
>>>>>
>>>>>
>>>>>
>>>>>
>>>>>
>>>>>
>>>>> Dear Kirill,
>>>>>
>>>>> I think the problem is in:
>>>>>
>>>>> ttt<-data.frame(q15,age, PUTIN_BI) # Step 1
>>>>> z.out <- zelig(PUTIN_BI ~ ttt$q15, ttt$age, na.exclude(ttt), model =
>>>>> "logit") # Step 2
>>>>>
>>>>> This should be, for the first step:
>>>>> ttt <- data.farme(q15 = q15, age = age, putin = PUTIN_BI)
>>>>> For the second step, I'm not sure what you're trying to do, but
>>>>> formulas should NEVER have $ in them! That confuses setx and sim to
>>>>> no end. And you should ALWAYS name every argument passed, since the
>>>>> order may vary. If you want to run a regression for putin on age and
>>>>> q15, then use
>>>>> z.out <- zelig(putin ~ age + q15, data = ttt, model = "logit")
>>>>> Note that I have named every argument after the default formula. You
>>>>> don't need to say na.exclude() yourself, as zelig() will do that
>>>>> automatically.
>>>>>
>>>>> If you are trying to use age as weights for observations (don't see
>>>>> why you would want to, though):
>>>>> ttt <- na.omit(ttt)
>>>>> z.out <- zelig(putin ~ q15, weights = ttt$age, data = ttt, model =
>>>>> "logit")
>>>>> You do need to do the list wise deletion yourself if you specify
>>>>> weights, and weights does need a $ in it to identify the data frame.
>>>>>
>>>>> Hope this helps, best,
>>>>> Olivia
>>>>>
>>>>>
>>>>>
>>>>>
>>>>> On 2/18/07, Kirill Kalinin <kkalinin(a)eu.spb.ru> wrote:
>>>>>> Dear Olivia,
>>>>>>
>>>>>> I am a PhD student with the European University at St. Petersburg,
>>>>>> working
>>>>>
>>>>>> on electoral behavior issues. The dataset I am running is huge -
>>>>>> 30000
>>>>>> cases. I look forward to calculating the first differences using
>>>>>> 'logit'
>>>>>> but when running setx() I get an error message: "Error: protect():
>>>>>> protection stack overflow". I was trying to decrease the size of
>>>>>> then
>>>>>> dataset, but it doesn't seem to help.
>>>>>> The script is as follows:
>>>>>>
>>>>>> library (Zelig)
>>>>>> library(foreign)
>>>>>>
>>>>>> Estdata <- read.spss(
>>>>>> "G:/geo_c.sav",
>>>>>> to.data.frame=T, use.value.labels=T)
>>>>>> dim(Estdata)
>>>>>> names(Estdata)
>>>>>> attach(Estdata)
>>>>>> q15<- as.ordered(Q15) #ordered categorical variable with 4
>>>>>> values (1-4)
>>>>>> age<-as.ordered(AGE) #ordered categorical variable with 4
>>>>>> values (1-4)
>>>>>> ttt<-data.frame(q15,age, PUTIN_BI)
>>>>>> z.out <- zelig(PUTIN_BI ~ ttt$q15, ttt$age, na.exclude(ttt), model =
>>>>>> "logit")
>>>>>>
>>>>>> Then I run:
>>>>>> x.low <- setx(z.out, q15=1)
>>>>>> x.high <- setx(z.out, q15=4)
>>>>>> So I get:
>>>>>> protect(): protection stack overflow
>>>>>>
>>>>>>
>>>>>> I wonder whether I am doing something wrong, as I am new to R and
>>>>>> Zelig,
>>>>> or
>>>>>> this happens because of my computer limitations. In fact,
>>>>>> everything is
>>>>>> perfect with metric variables, this problem occurs just with the
>>>>>> ordered
>>>>>> categorical variables. Could you help me to resolve the issue?
>>>>>>
>>>>>> Thank you very much!
>>>>>>
>>>>>> All the Best,
>>>>>> Kirill
>>>>>> P.S. Happy Chinese New Year!
>>>>>>
>>>>>>
>>>>>
>>>>
>>>>
>>>>
>>>
>>>
>>>
>>>
>>>
>>>
>>
>>
>>
>
>
-
Zelig Mailing List, served by Harvard-MIT Data Center
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If you use multiply-imputed data sets, zelig() will run the model on each
imputed data set and returns an output, which is a list. You can extract
each output by, for example,
z.out[[1]]
If you want coefficients for the model fitted to the second imputed
data set, then you can do
z.out[[2]]$coef
etc.
Kosuke
-----------------------------------------------------
Kosuke Imai Office: Corwin Hall 041
Assistant Professor Phone: 609-258-6601
Department of Politics eFax: 973-556-1929
Princeton University Email: kimai(a)Princeton.Edu
Princeton, NJ 08544-1012 http://imai.princeton.edu
-----------------------------------------------------
On Fri, 23 Feb 2007, Anders Schwartz Corr wrote:
>
> Hi Kosuke,
>
> Olivia is in NZ ... do you know how to check my residuals on Zelig with
> multiply imputed datasets? This can wait until Olivia returns. See below.
>
> Thanks,
>
> Anders
>
> ---------- Forwarded message ----------
> Date: Fri, 23 Feb 2007 21:45:56 +1300
> From: Olivia Lau <olau(a)fas.harvard.edu>
> To: Anders Schwartz Corr <corr(a)fas.harvard.edu>
> Subject: Re: question
>
> that's because you did it on multiply imputed datasets. I'm in New
> Zealand right now and I can't do anything about this -- I don't have
> server access. why don't you email kosuke? Thanks, O
>
> On 2/23/07, Anders Schwartz Corr <corr(a)fas.harvard.edu> wrote:
>>
>> Hi Olivia,
>>
>> Not sure how to get my residuals. My attempts are below. z.out$coef does
>> not seem to work as stated on the Zelig website:
>>
>> http://gking.harvard.edu/zelig/docs/Output_Values12.html
>>
>> Thanks
>>
>> Anders
>>
>> > summary(z.out)
>>
>> Model: normal
>> Number of multiply imputed data sets: 5
>>
>> Combined results:
>>
>> Call:
>> zelig(formula = ncc13 ~ p_norm_total + exp(p_norm_total) + year +
>> demo + exp(demo) + fed + exp(fed) + gpconcsq + dems6/num_stat +
>> cinc/ter + tradeope_log + elf85 + contgain.merge1 + contlose.loser +
>> gdpcap_1000 + popden_1000 + upopprct, model = "normal", data =
>> imputeddata2)
>>
>> Coefficients:
>> Value Std. Error t-stat p-value
>> (Intercept) 7.382e+03 6.915e+04 0.10675 0.91610
>> p_norm_total 4.843e+04 5.326e+04 0.90934 0.38935
>> exp(p_norm_total) -2.542e+04 3.274e+04 -0.77664 0.45650
>> year 2.518e+01 5.001e+01 0.50357 0.62875
>> demo 4.535e+02 2.117e+02 2.14225 0.04859
>> exp(demo) -1.017e-05 2.182e-05 -0.46599 0.65098
>> fed 3.298e+03 5.756e+03 0.57305 0.57427
>> exp(fed) -1.155e+02 2.024e+03 -0.05706 0.95517
>> gpconcsq -3.302e+04 7.125e+04 -0.46345 0.65814
>> dems6 -2.208e+02 3.382e+02 -0.65297 0.52256
>> cinc 9.043e+03 4.292e+04 0.21071 0.83599
>> tradeope_log 1.313e+03 4.798e+03 0.27359 0.79499
>> elf85 -3.891e+03 5.399e+03 -0.72059 0.48722
>> contgain.merge1 2.395e+03 7.210e+03 0.33219 0.75379
>> contlose.loser 3.303e+03 8.207e+03 0.40240 0.70557
>> gdpcap_1000 2.160e+02 3.654e+02 0.59115 0.57263
>> popden_1000 2.958e+01 2.937e+02 0.10073 0.92011
>> upopprct -1.024e+04 3.053e+04 -0.33538 0.75185
>> dems6:num_stat -1.577e-01 2.414e+00 -0.06532 0.94923
>> cinc:ter 2.498e+02 4.654e+02 0.53669 0.60042
>>
>> For combined results from datasets i to j, use summary(x, subset = i:j).
>> For separate results, use print(summary(x), subset = i:j).
>>
>> > z.out$coef
>> NULL
>> > z.out$residuals
>> NULL
>> > summary(residuals)
>> Error in object[[i]] : object is not subsettable
>> > residuals
>> function (object, ...)
>> UseMethod("residuals")
>> <environment: namespace:stats>
>> >
>>
>>
>>
>
-
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Zelig program information: http://gking.harvard.edu/zelig/
yes, it's the usual confidence interval on the quantity of interest and so
your interpretation is correct. There is no option, currently, in sim()
that lets you calculate the p-values, but you can do it by hand. For
example, you can do mean(s.out$fd > 0) to calculate the proportion of
simulation draws that are greater than 0.
Kosuke
On Fri, 23 Feb 2007, Kirill Kalinin wrote:
> Dear Kosuke,
>
> Thank you a lot for your prompt reply! It's great that I can use it to work
> with the percentages. I wonder if the confidence interval which I got in the
> output below can be interpreted as usual, so that the null hypothesis can't
> be rejected at 0.05 level, is this correct? Also I wonder is there an
> option in sim() to get confidence intervals together with p-values, so as it
> could be easier to deal with the 'first differences' signficance.
>
> ----------------Output----------------------------
> First Differences in Expected Values: E(Y|X1)-E(Y|X)
> mean sd 2.5% 97.5%
> 1 0.00973 0.01058 -0.01066 0.03029
> --------------------------------------------------
> Thank you a lot for your help!
>
> All the best,
> Kirill
>
>
>
> ----------------------------------------
>> Thank you very much for you help on my matter. Actually, I need to
>> calculate the difference in the predicted probabilities of Russian
>> voters choosing Putin when explanatory variable shifts from its minimum
>> to its maximum value, holding other terms in the equation constant at
>> their medians. I am trying to get everything right: could you tell me
>> what 'Mean' in first differences stand for?
>
> Zelig simulates the quantities of interest and so "Mean" is the mean of
> this simulated quantitites (the default is 1000 simulations). You can
> think of it as a point estimate of the quantity of interest.
>
>> Another important question is: if I have 10 variables, for example, and
>> calculate first differences, holding the rest at their medians, will all
>> 'first differences' sum up to "0" and predicted probabilities to "1"? If
>> so, it could help me to claim that, say, the value of 0.15 in first
>> differences between young and old would give Putin 15% of the vote! If
>> not so, is it hard to make it Zelig? In fact, I am trying to follow T.
>> Colton's approach in "Transitional citizens" (2000), so as I could
>> compare my calculations with his as well. And, finally do you know about
>> any book for beginners to help to understand simulation techniques with
>> Zelig? It's a new promising field for me!
>
> Yes, your interpretation is correct. The first differences should sum up
> to and the predicted probabilities sum up to 1 in the case of the
> logit/probit if that's what you are using.
>
> Kosuke
>
>>
>> All the best,
>> Kirill
>>
>> -------------------------------------------------
>> it's already on our website - it will take a few days for it to appear at
>> CRAN. Try:
>>
>> install.packages("Zelig", repos = "http://gking.harvard.edu")
>>
>> Kosuke
>>
>> -----------------------------------------------------
>> Kosuke Imai Office: Corwin Hall 041
>> Assistant Professor Phone: 609-258-6601
>> Department of Politics eFax: 973-556-1929
>> Princeton University Email: kimai(a)Princeton.Edu
>> Princeton, NJ 08544-1012 http://imai.princeton.edu
>> -----------------------------------------------------
>>
>> On Wed, 21 Feb 2007, Kirill Kalinin wrote:
>>
>>> Dear Kosuke,
>>>
>>> Thank you for your help! I'll be downloading a new version from
>>> www.r-project.org later today.
>>>
>>> All the best,
>>> Kirill
>>>
>>>
>>>
>>>
>>> Dear Kirill,
>>>
>>> Thanks for the bug report. We've fixed this problem and will
>>> release a new version later today.
>>>
>>> Many thanks,
>>> Kosuke
>>>
>>> ---------------------------------------------------------
>>> Kosuke Imai Office: Corwin Hall 041
>>> Assistant Professor Phone: 609-258-6601
>>> Department of Politics Fax: 973-556-1929
>>> Princeton University Email: kimai(a)Princeton.Edu
>>> Princeton, NJ 08544-1012 http://imai.princeton.edu
>>> ---------------------------------------------------------
>>>
>>>
>>>
>>> On Feb 20, 2007, at 9:03 AM, Kirill Kalinin wrote:
>>>
>>>> Dear Kosuke,
>>>>
>>>> Olivia advised me to address my problem to you, which is when I am
>>>> trying to
>>>> run setx() with the ordered catagorical variables (metric variables
>>>> work
>>>> fine) in 'logit' model I get "Error: protect(): protection stack
>>>> overflow".
>>>> What might be the solution to the problem?
>>>>
>>>> Thank you a lot for your help!
>>>>
>>>> Best regards,
>>>> Kirill
>>>>
>>>> --------------------------------------
>>>>
>>>>
>>>>> Dear Olivia,
>>>>>
>>>>> Thank you a lot for your prompt and detailed reply! Well, I
>>>>> changed the
>>>>> script as you advised to, but it doesn't seem to help to resolve the
>>>>> issue. Same error appears when I am trying to run setx(). Are there
>>>>> any other suggestions of what might be wrong with the script?
>>>>>
>>>>> Here is what I'm getting on my console now:
>>>>>
>>>>>> q15<- as.ordered(Q15)
>>>>>> age<-as.ordered(AGE)
>>>>>> ttt<-data.frame(q15=q15,age=age, putin=PUTIN_BI)
>>>>>> z.out <- zelig(putin ~ age + q15, data = ttt, model = "logit")
>>>>>> x.low <- setx(z.out, age = 1)
>>>>> Error: protect(): protection stack overflow
>>>>>> x.high <- setx(z.out, age = 4)
>>>>> Error: protect(): protection stack overflow
>>>>>
>>>>> Thank you a lot for you help!
>>>>> Best wishes,
>>>>> Kirill
>>>>>
>>>>>
>>>>
>>>>
>>>>
>>>>
>>>>
>>>>
>>>> Dear Kirill,
>>>>
>>>> I think the problem is in:
>>>>
>>>> ttt<-data.frame(q15,age, PUTIN_BI) # Step 1
>>>> z.out <- zelig(PUTIN_BI ~ ttt$q15, ttt$age, na.exclude(ttt), model =
>>>> "logit") # Step 2
>>>>
>>>> This should be, for the first step:
>>>> ttt <- data.farme(q15 = q15, age = age, putin = PUTIN_BI)
>>>> For the second step, I'm not sure what you're trying to do, but
>>>> formulas should NEVER have $ in them! That confuses setx and sim to
>>>> no end. And you should ALWAYS name every argument passed, since the
>>>> order may vary. If you want to run a regression for putin on age and
>>>> q15, then use
>>>> z.out <- zelig(putin ~ age + q15, data = ttt, model = "logit")
>>>> Note that I have named every argument after the default formula. You
>>>> don't need to say na.exclude() yourself, as zelig() will do that
>>>> automatically.
>>>>
>>>> If you are trying to use age as weights for observations (don't see
>>>> why you would want to, though):
>>>> ttt <- na.omit(ttt)
>>>> z.out <- zelig(putin ~ q15, weights = ttt$age, data = ttt, model =
>>>> "logit")
>>>> You do need to do the list wise deletion yourself if you specify
>>>> weights, and weights does need a $ in it to identify the data frame.
>>>>
>>>> Hope this helps, best,
>>>> Olivia
>>>>
>>>>
>>>>
>>>>
>>>> On 2/18/07, Kirill Kalinin <kkalinin(a)eu.spb.ru> wrote:
>>>>> Dear Olivia,
>>>>>
>>>>> I am a PhD student with the European University at St. Petersburg,
>>>>> working
>>>>
>>>>> on electoral behavior issues. The dataset I am running is huge -
>>>>> 30000
>>>>> cases. I look forward to calculating the first differences using
>>>>> 'logit'
>>>>> but when running setx() I get an error message: "Error: protect():
>>>>> protection stack overflow". I was trying to decrease the size of
>>>>> then
>>>>> dataset, but it doesn't seem to help.
>>>>> The script is as follows:
>>>>>
>>>>> library (Zelig)
>>>>> library(foreign)
>>>>>
>>>>> Estdata <- read.spss(
>>>>> "G:/geo_c.sav",
>>>>> to.data.frame=T, use.value.labels=T)
>>>>> dim(Estdata)
>>>>> names(Estdata)
>>>>> attach(Estdata)
>>>>> q15<- as.ordered(Q15) #ordered categorical variable with 4
>>>>> values (1-4)
>>>>> age<-as.ordered(AGE) #ordered categorical variable with 4
>>>>> values (1-4)
>>>>> ttt<-data.frame(q15,age, PUTIN_BI)
>>>>> z.out <- zelig(PUTIN_BI ~ ttt$q15, ttt$age, na.exclude(ttt), model =
>>>>> "logit")
>>>>>
>>>>> Then I run:
>>>>> x.low <- setx(z.out, q15=1)
>>>>> x.high <- setx(z.out, q15=4)
>>>>> So I get:
>>>>> protect(): protection stack overflow
>>>>>
>>>>>
>>>>> I wonder whether I am doing something wrong, as I am new to R and
>>>>> Zelig,
>>>> or
>>>>> this happens because of my computer limitations. In fact,
>>>>> everything is
>>>>> perfect with metric variables, this problem occurs just with the
>>>>> ordered
>>>>> categorical variables. Could you help me to resolve the issue?
>>>>>
>>>>> Thank you very much!
>>>>>
>>>>> All the Best,
>>>>> Kirill
>>>>> P.S. Happy Chinese New Year!
>>>>>
>>>>>
>>>>
>>>
>>>
>>>
>>
>>
>>
>>
>>
>>
>
>
>
-
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> Thank you very much for you help on my matter. Actually, I need to
> calculate the difference in the predicted probabilities of Russian
> voters choosing Putin when explanatory variable shifts from its minimum
> to its maximum value, holding other terms in the equation constant at
> their medians. I am trying to get everything right: could you tell me
> what 'Mean' in first differences stand for?
Zelig simulates the quantities of interest and so "Mean" is the mean of
this simulated quantitites (the default is 1000 simulations). You can
think of it as a point estimate of the quantity of interest.
> Another important question is: if I have 10 variables, for example, and
> calculate first differences, holding the rest at their medians, will all
> 'first differences' sum up to "0" and predicted probabilities to "1"? If
> so, it could help me to claim that, say, the value of 0.15 in first
> differences between young and old would give Putin 15% of the vote! If
> not so, is it hard to make it Zelig? In fact, I am trying to follow T.
> Colton's approach in "Transitional citizens" (2000), so as I could
> compare my calculations with his as well. And, finally do you know about
> any book for beginners to help to understand simulation techniques with
> Zelig? It's a new promising field for me!
Yes, your interpretation is correct. The first differences should sum up
to and the predicted probabilities sum up to 1 in the case of the
logit/probit if that's what you are using.
Kosuke
>
> All the best,
> Kirill
>
> -------------------------------------------------
> it's already on our website - it will take a few days for it to appear at
> CRAN. Try:
>
> install.packages("Zelig", repos = "http://gking.harvard.edu")
>
> Kosuke
>
> -----------------------------------------------------
> Kosuke Imai Office: Corwin Hall 041
> Assistant Professor Phone: 609-258-6601
> Department of Politics eFax: 973-556-1929
> Princeton University Email: kimai(a)Princeton.Edu
> Princeton, NJ 08544-1012 http://imai.princeton.edu
> -----------------------------------------------------
>
> On Wed, 21 Feb 2007, Kirill Kalinin wrote:
>
>> Dear Kosuke,
>>
>> Thank you for your help! I'll be downloading a new version from
>> www.r-project.org later today.
>>
>> All the best,
>> Kirill
>>
>>
>>
>>
>> Dear Kirill,
>>
>> Thanks for the bug report. We've fixed this problem and will
>> release a new version later today.
>>
>> Many thanks,
>> Kosuke
>>
>> ---------------------------------------------------------
>> Kosuke Imai Office: Corwin Hall 041
>> Assistant Professor Phone: 609-258-6601
>> Department of Politics Fax: 973-556-1929
>> Princeton University Email: kimai(a)Princeton.Edu
>> Princeton, NJ 08544-1012 http://imai.princeton.edu
>> ---------------------------------------------------------
>>
>>
>>
>> On Feb 20, 2007, at 9:03 AM, Kirill Kalinin wrote:
>>
>>> Dear Kosuke,
>>>
>>> Olivia advised me to address my problem to you, which is when I am
>>> trying to
>>> run setx() with the ordered catagorical variables (metric variables
>>> work
>>> fine) in 'logit' model I get "Error: protect(): protection stack
>>> overflow".
>>> What might be the solution to the problem?
>>>
>>> Thank you a lot for your help!
>>>
>>> Best regards,
>>> Kirill
>>>
>>> --------------------------------------
>>>
>>>
>>>> Dear Olivia,
>>>>
>>>> Thank you a lot for your prompt and detailed reply! Well, I
>>>> changed the
>>>> script as you advised to, but it doesn't seem to help to resolve the
>>>> issue. Same error appears when I am trying to run setx(). Are there
>>>> any other suggestions of what might be wrong with the script?
>>>>
>>>> Here is what I'm getting on my console now:
>>>>
>>>>> q15<- as.ordered(Q15)
>>>>> age<-as.ordered(AGE)
>>>>> ttt<-data.frame(q15=q15,age=age, putin=PUTIN_BI)
>>>>> z.out <- zelig(putin ~ age + q15, data = ttt, model = "logit")
>>>>> x.low <- setx(z.out, age = 1)
>>>> Error: protect(): protection stack overflow
>>>>> x.high <- setx(z.out, age = 4)
>>>> Error: protect(): protection stack overflow
>>>>
>>>> Thank you a lot for you help!
>>>> Best wishes,
>>>> Kirill
>>>>
>>>>
>>>
>>>
>>>
>>>
>>>
>>>
>>> Dear Kirill,
>>>
>>> I think the problem is in:
>>>
>>> ttt<-data.frame(q15,age, PUTIN_BI) # Step 1
>>> z.out <- zelig(PUTIN_BI ~ ttt$q15, ttt$age, na.exclude(ttt), model =
>>> "logit") # Step 2
>>>
>>> This should be, for the first step:
>>> ttt <- data.farme(q15 = q15, age = age, putin = PUTIN_BI)
>>> For the second step, I'm not sure what you're trying to do, but
>>> formulas should NEVER have $ in them! That confuses setx and sim to
>>> no end. And you should ALWAYS name every argument passed, since the
>>> order may vary. If you want to run a regression for putin on age and
>>> q15, then use
>>> z.out <- zelig(putin ~ age + q15, data = ttt, model = "logit")
>>> Note that I have named every argument after the default formula. You
>>> don't need to say na.exclude() yourself, as zelig() will do that
>>> automatically.
>>>
>>> If you are trying to use age as weights for observations (don't see
>>> why you would want to, though):
>>> ttt <- na.omit(ttt)
>>> z.out <- zelig(putin ~ q15, weights = ttt$age, data = ttt, model =
>>> "logit")
>>> You do need to do the list wise deletion yourself if you specify
>>> weights, and weights does need a $ in it to identify the data frame.
>>>
>>> Hope this helps, best,
>>> Olivia
>>>
>>>
>>>
>>>
>>> On 2/18/07, Kirill Kalinin <kkalinin(a)eu.spb.ru> wrote:
>>>> Dear Olivia,
>>>>
>>>> I am a PhD student with the European University at St. Petersburg,
>>>> working
>>>
>>>> on electoral behavior issues. The dataset I am running is huge -
>>>> 30000
>>>> cases. I look forward to calculating the first differences using
>>>> 'logit'
>>>> but when running setx() I get an error message: "Error: protect():
>>>> protection stack overflow". I was trying to decrease the size of
>>>> then
>>>> dataset, but it doesn't seem to help.
>>>> The script is as follows:
>>>>
>>>> library (Zelig)
>>>> library(foreign)
>>>>
>>>> Estdata <- read.spss(
>>>> "G:/geo_c.sav",
>>>> to.data.frame=T, use.value.labels=T)
>>>> dim(Estdata)
>>>> names(Estdata)
>>>> attach(Estdata)
>>>> q15<- as.ordered(Q15) #ordered categorical variable with 4
>>>> values (1-4)
>>>> age<-as.ordered(AGE) #ordered categorical variable with 4
>>>> values (1-4)
>>>> ttt<-data.frame(q15,age, PUTIN_BI)
>>>> z.out <- zelig(PUTIN_BI ~ ttt$q15, ttt$age, na.exclude(ttt), model =
>>>> "logit")
>>>>
>>>> Then I run:
>>>> x.low <- setx(z.out, q15=1)
>>>> x.high <- setx(z.out, q15=4)
>>>> So I get:
>>>> protect(): protection stack overflow
>>>>
>>>>
>>>> I wonder whether I am doing something wrong, as I am new to R and
>>>> Zelig,
>>> or
>>>> this happens because of my computer limitations. In fact,
>>>> everything is
>>>> perfect with metric variables, this problem occurs just with the
>>>> ordered
>>>> categorical variables. Could you help me to resolve the issue?
>>>>
>>>> Thank you very much!
>>>>
>>>> All the Best,
>>>> Kirill
>>>> P.S. Happy Chinese New Year!
>>>>
>>>>
>>>
>>
>>
>>
>
>
>
>
>
>
-
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Vinh Nguyen wrote:
> I believe the authors made zelig take in a factor response in zelig and then
> passing it on. Just part of the code I think, nothing big.
Hmm, does not make sense that as.factor(y) needs to be called
nevertheless y is already a factor.
Gregor
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it's already on our website - it will take a few days for it to appear at
CRAN. Try:
install.packages("Zelig", repos = "http://gking.harvard.edu")
Kosuke
-----------------------------------------------------
Kosuke Imai Office: Corwin Hall 041
Assistant Professor Phone: 609-258-6601
Department of Politics eFax: 973-556-1929
Princeton University Email: kimai(a)Princeton.Edu
Princeton, NJ 08544-1012 http://imai.princeton.edu
-----------------------------------------------------
On Wed, 21 Feb 2007, Kirill Kalinin wrote:
> Dear Kosuke,
>
> Thank you for your help! I'll be downloading a new version from
> www.r-project.org later today.
>
> All the best,
> Kirill
>
>
>
>
> Dear Kirill,
>
> Thanks for the bug report. We've fixed this problem and will
> release a new version later today.
>
> Many thanks,
> Kosuke
>
> ---------------------------------------------------------
> Kosuke Imai Office: Corwin Hall 041
> Assistant Professor Phone: 609-258-6601
> Department of Politics Fax: 973-556-1929
> Princeton University Email: kimai(a)Princeton.Edu
> Princeton, NJ 08544-1012 http://imai.princeton.edu
> ---------------------------------------------------------
>
>
>
> On Feb 20, 2007, at 9:03 AM, Kirill Kalinin wrote:
>
>> Dear Kosuke,
>>
>> Olivia advised me to address my problem to you, which is when I am
>> trying to
>> run setx() with the ordered catagorical variables (metric variables
>> work
>> fine) in 'logit' model I get "Error: protect(): protection stack
>> overflow".
>> What might be the solution to the problem?
>>
>> Thank you a lot for your help!
>>
>> Best regards,
>> Kirill
>>
>> --------------------------------------
>>
>>
>>> Dear Olivia,
>>>
>>> Thank you a lot for your prompt and detailed reply! Well, I
>>> changed the
>>> script as you advised to, but it doesn't seem to help to resolve the
>>> issue. Same error appears when I am trying to run setx(). Are there
>>> any other suggestions of what might be wrong with the script?
>>>
>>> Here is what I'm getting on my console now:
>>>
>>>> q15<- as.ordered(Q15)
>>>> age<-as.ordered(AGE)
>>>> ttt<-data.frame(q15=q15,age=age, putin=PUTIN_BI)
>>>> z.out <- zelig(putin ~ age + q15, data = ttt, model = "logit")
>>>> x.low <- setx(z.out, age = 1)
>>> Error: protect(): protection stack overflow
>>>> x.high <- setx(z.out, age = 4)
>>> Error: protect(): protection stack overflow
>>>
>>> Thank you a lot for you help!
>>> Best wishes,
>>> Kirill
>>>
>>>
>>
>>
>>
>>
>>
>>
>> Dear Kirill,
>>
>> I think the problem is in:
>>
>> ttt<-data.frame(q15,age, PUTIN_BI) # Step 1
>> z.out <- zelig(PUTIN_BI ~ ttt$q15, ttt$age, na.exclude(ttt), model =
>> "logit") # Step 2
>>
>> This should be, for the first step:
>> ttt <- data.farme(q15 = q15, age = age, putin = PUTIN_BI)
>> For the second step, I'm not sure what you're trying to do, but
>> formulas should NEVER have $ in them! That confuses setx and sim to
>> no end. And you should ALWAYS name every argument passed, since the
>> order may vary. If you want to run a regression for putin on age and
>> q15, then use
>> z.out <- zelig(putin ~ age + q15, data = ttt, model = "logit")
>> Note that I have named every argument after the default formula. You
>> don't need to say na.exclude() yourself, as zelig() will do that
>> automatically.
>>
>> If you are trying to use age as weights for observations (don't see
>> why you would want to, though):
>> ttt <- na.omit(ttt)
>> z.out <- zelig(putin ~ q15, weights = ttt$age, data = ttt, model =
>> "logit")
>> You do need to do the list wise deletion yourself if you specify
>> weights, and weights does need a $ in it to identify the data frame.
>>
>> Hope this helps, best,
>> Olivia
>>
>>
>>
>>
>> On 2/18/07, Kirill Kalinin <kkalinin(a)eu.spb.ru> wrote:
>>> Dear Olivia,
>>>
>>> I am a PhD student with the European University at St. Petersburg,
>>> working
>>
>>> on electoral behavior issues. The dataset I am running is huge -
>>> 30000
>>> cases. I look forward to calculating the first differences using
>>> 'logit'
>>> but when running setx() I get an error message: "Error: protect():
>>> protection stack overflow". I was trying to decrease the size of
>>> then
>>> dataset, but it doesn't seem to help.
>>> The script is as follows:
>>>
>>> library (Zelig)
>>> library(foreign)
>>>
>>> Estdata <- read.spss(
>>> "G:/geo_c.sav",
>>> to.data.frame=T, use.value.labels=T)
>>> dim(Estdata)
>>> names(Estdata)
>>> attach(Estdata)
>>> q15<- as.ordered(Q15) #ordered categorical variable with 4
>>> values (1-4)
>>> age<-as.ordered(AGE) #ordered categorical variable with 4
>>> values (1-4)
>>> ttt<-data.frame(q15,age, PUTIN_BI)
>>> z.out <- zelig(PUTIN_BI ~ ttt$q15, ttt$age, na.exclude(ttt), model =
>>> "logit")
>>>
>>> Then I run:
>>> x.low <- setx(z.out, q15=1)
>>> x.high <- setx(z.out, q15=4)
>>> So I get:
>>> protect(): protection stack overflow
>>>
>>>
>>> I wonder whether I am doing something wrong, as I am new to R and
>>> Zelig,
>> or
>>> this happens because of my computer limitations. In fact,
>>> everything is
>>> perfect with metric variables, this problem occurs just with the
>>> ordered
>>> categorical variables. Could you help me to resolve the issue?
>>>
>>> Thank you very much!
>>>
>>> All the Best,
>>> Kirill
>>> P.S. Happy Chinese New Year!
>>>
>>>
>>
>
>
>
-
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Hello!
I just started with zelig and find it very convenient! I played with
mlogit model and I wonder why I have to use as.factor() for dependent
variable y no matter if this is already a factor. I show this with
mexico data bellow with Zelig (Version 2.7-5, built: 2006-12-25)
> library(package="Zelig")
> data(mexico)
## as shown in documentation
> z.out1 <- zelig(as.factor(vote88) ~ pristr + othcok + othsocok,
model = "mlogit", data = mexico)
## all OK
## now let us try without as.factor, but specifying y as factor before!
> mexico$vote88 <- factor(mexico$vote88)
> z.out1 <- zelig(vote88 ~ pristr + othcok + othsocok,
+ model="mlogit", data=mexico)
Error in dimnames(xbig) <- list(vlabel(yn, rep(M, n), M), vlabel(xn,
ncolBlist, :
length of 'dimnames' [1] not equal to array extent
## ???
--
Lep pozdrav / With regards,
Gregor Gorjanc
----------------------------------------------------------------------
University of Ljubljana PhD student
Biotechnical Faculty
Zootechnical Department URI: http://www.bfro.uni-lj.si/MR/ggorjan
Groblje 3 mail: gregor.gorjanc <at> bfro.uni-lj.si
SI-1230 Domzale tel: +386 (0)1 72 17 861
Slovenia, Europe fax: +386 (0)1 72 17 888
----------------------------------------------------------------------
"One must learn by doing the thing; for though you think you know it,
you have no certainty until you try." Sophocles ~ 450 B.C.
----------------------------------------------------------------------
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Dear Kirill,
Thanks for the bug report. We've fixed this problem and will
release a new version later today.
Many thanks,
Kosuke
---------------------------------------------------------
Kosuke Imai Office: Corwin Hall 041
Assistant Professor Phone: 609-258-6601
Department of Politics Fax: 973-556-1929
Princeton University Email: kimai(a)Princeton.Edu
Princeton, NJ 08544-1012 http://imai.princeton.edu
---------------------------------------------------------
On Feb 20, 2007, at 9:03 AM, Kirill Kalinin wrote:
> Dear Kosuke,
>
> Olivia advised me to address my problem to you, which is when I am
> trying to
> run setx() with the ordered catagorical variables (metric variables
> work
> fine) in 'logit' model I get "Error: protect(): protection stack
> overflow".
> What might be the solution to the problem?
>
> Thank you a lot for your help!
>
> Best regards,
> Kirill
>
> --------------------------------------
>
>
>> Dear Olivia,
>>
>> Thank you a lot for your prompt and detailed reply! Well, I
>> changed the
>> script as you advised to, but it doesn't seem to help to resolve the
>> issue. Same error appears when I am trying to run setx(). Are there
>> any other suggestions of what might be wrong with the script?
>>
>> Here is what I'm getting on my console now:
>>
>>> q15<- as.ordered(Q15)
>>> age<-as.ordered(AGE)
>>> ttt<-data.frame(q15=q15,age=age, putin=PUTIN_BI)
>>> z.out <- zelig(putin ~ age + q15, data = ttt, model = "logit")
>>> x.low <- setx(z.out, age = 1)
>> Error: protect(): protection stack overflow
>>> x.high <- setx(z.out, age = 4)
>> Error: protect(): protection stack overflow
>>
>> Thank you a lot for you help!
>> Best wishes,
>> Kirill
>>
>>
>
>
>
>
>
>
> Dear Kirill,
>
> I think the problem is in:
>
> ttt<-data.frame(q15,age, PUTIN_BI) # Step 1
> z.out <- zelig(PUTIN_BI ~ ttt$q15, ttt$age, na.exclude(ttt), model =
> "logit") # Step 2
>
> This should be, for the first step:
> ttt <- data.farme(q15 = q15, age = age, putin = PUTIN_BI)
> For the second step, I'm not sure what you're trying to do, but
> formulas should NEVER have $ in them! That confuses setx and sim to
> no end. And you should ALWAYS name every argument passed, since the
> order may vary. If you want to run a regression for putin on age and
> q15, then use
> z.out <- zelig(putin ~ age + q15, data = ttt, model = "logit")
> Note that I have named every argument after the default formula. You
> don't need to say na.exclude() yourself, as zelig() will do that
> automatically.
>
> If you are trying to use age as weights for observations (don't see
> why you would want to, though):
> ttt <- na.omit(ttt)
> z.out <- zelig(putin ~ q15, weights = ttt$age, data = ttt, model =
> "logit")
> You do need to do the list wise deletion yourself if you specify
> weights, and weights does need a $ in it to identify the data frame.
>
> Hope this helps, best,
> Olivia
>
>
>
>
> On 2/18/07, Kirill Kalinin <kkalinin(a)eu.spb.ru> wrote:
>> Dear Olivia,
>>
>> I am a PhD student with the European University at St. Petersburg,
>> working
>
>> on electoral behavior issues. The dataset I am running is huge -
>> 30000
>> cases. I look forward to calculating the first differences using
>> 'logit'
>> but when running setx() I get an error message: "Error: protect():
>> protection stack overflow". I was trying to decrease the size of
>> then
>> dataset, but it doesn't seem to help.
>> The script is as follows:
>>
>> library (Zelig)
>> library(foreign)
>>
>> Estdata <- read.spss(
>> "G:/geo_c.sav",
>> to.data.frame=T, use.value.labels=T)
>> dim(Estdata)
>> names(Estdata)
>> attach(Estdata)
>> q15<- as.ordered(Q15) #ordered categorical variable with 4
>> values (1-4)
>> age<-as.ordered(AGE) #ordered categorical variable with 4
>> values (1-4)
>> ttt<-data.frame(q15,age, PUTIN_BI)
>> z.out <- zelig(PUTIN_BI ~ ttt$q15, ttt$age, na.exclude(ttt), model =
>> "logit")
>>
>> Then I run:
>> x.low <- setx(z.out, q15=1)
>> x.high <- setx(z.out, q15=4)
>> So I get:
>> protect(): protection stack overflow
>>
>>
>> I wonder whether I am doing something wrong, as I am new to R and
>> Zelig,
> or
>> this happens because of my computer limitations. In fact,
>> everything is
>> perfect with metric variables, this problem occurs just with the
>> ordered
>> categorical variables. Could you help me to resolve the issue?
>>
>> Thank you very much!
>>
>> All the Best,
>> Kirill
>> P.S. Happy Chinese New Year!
>>
>>
>
-
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