Re: [amelia] Example for ameliabind?

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W. D.

14 Nov 2015 14 Nov '15

3:28 p.m.

At 22:40 11/12/2015, W. D. wrote:

...

At 21:30 11/12/2015, Matt Blackwell wrote:

Hi there,Â I actually don't think you actually need to use ameliabind() here.

The amelia output already has all of the datasets together. It might help us to know what is it that you want to accomplish with ameliabind() in this case.

Cheers, Matt

Thanks, Matt. I'm just trying to do a plain old linear regression.

I had to export the data to 5 text files and combine them manually, deleting the extra header records. I then imported the combined, imputed data and ran a regression: lm.ImputedDataAll5 <- lm(DepVar ~ IndVar1 + IndVar2 + IndVar3 + IndVar4 + IndVar5, data=ImputedDataAll5) Is there some way to skip the manual editing steps and use the imputed data structure with lm? Thanks for any light you can shed.

...

I tried going the ameliabind() route because when trying to use lm() with the 5 sets of imputed data, I get the following error: Error in as.data.frame.default(data) : cannot coerce class ""amelia"" to a data.frame Would you please let me know the proper way to regress these 5 datasets? Thanks!

On Thu, Nov 12, 2015 at 10:11 PM, W. D. <<mailto:WD@a7h.com>WD@a7h.com> wrote: At 06:47 11/11/2015, Matt Blackwell wrote: >Hi there,Ã > >The 5 imputed datasets are actually contained in the DataImputed

object and you can access each imputed dataset like so:

> >DataImputed$imputations[[1]] >DataImputed$imputations[[2]] > >And so on. ameliabind() will merge the output of two amelia() calls

into 1 so that if each had 5 imputed datasets, then the binded object will have 10.Ã

Thanks for the clue, Matt. However when I run: DataImputedAll <- ameliabind(DataImputed$imputations[[1]],

DataImputed$imputations[[2]], DataImputed$imputations[[3]], DataImputed$imputations[[4]], DataImputed$imputations[[5]])

It rudely spits out: "All arguments must be amelia output." When searching for that particular error, there isn't anything useful. What do you suggest? Thanks for your assistance! >Hope that helps! > >Cheers, >Matt > >~~~~~~~~~~~ >Matthew Blackwell >Assistant Professor of Government >Harvard University >url:

<<http://www.mattblackwell.org>http://www.mattblackwell.org>http://www .mattblackwell.orgÃ

> >On Wed, Nov 11, 2015 at 1:14 AM, W. D.

<<mailto:WD@a7h.com><mailto:WD@a7h.com>WD@a7h.com> wrote:

>If 5 sets of data are generated using a command like >this: > >DataImputed <- amelia(x=GroupData,incheck=TRUE) > >What would be the names of the 5 sets of data in order >to use ameliabind? > >DataImputedAll <- ameliabind(set1?, set2?, set3?, set4?, set5?) > >There seem to be a dearth of examples online. > >Thanks for your help. > >-- >Amelia mailing list served by HUIT >[Un]Subscribe/View Archive:

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Ista Zahn

14 Nov 14 Nov

5:14 p.m.

New subject: Example for ameliabind?

It doesn't make sense statistically to fit models to the combined data like that. Instead you should fit your model separately to each imputed dataset and then aggregate the estimates and standard errors across the model fits. There are R packages that will do this for you, see e.g., Zelig and mitools packages and section 4.10 in the Amelia package vignette. Best, Ista On Nov 14, 2015 3:29 PM, "W. D." <WD(a)a7h.com> wrote:

...

At 22:40 11/12/2015, W. D. wrote:

At 21:30 11/12/2015, Matt Blackwell wrote:

Hi there,Â I actually don't think you actually need to use ameliabind() here.

The amelia output already has all of the datasets together. It might help us to know what is it that you want to accomplish with ameliabind() in this case.

Cheers, Matt

Thanks, Matt. I'm just trying to do a plain old linear regression.

wrote:

At 06:47 11/11/2015, Matt Blackwell wrote: >Hi there,Ã‚ > >The 5 imputed datasets are actually contained in the DataImputed

object and you can access each imputed dataset like so:

> >DataImputed$imputations[[1]] >DataImputed$imputations[[2]] > >And so on. ameliabind() will merge the output of two amelia() calls

into 1 so that if each had 5 imputed datasets, then the binded object will have 10.Ã‚

Thanks for the clue, Matt. However when I run: DataImputedAll <- ameliabind(DataImputed$imputations[[1]],

DataImputed$imputations[[2]], DataImputed$imputations[[3]], DataImputed$imputations[[4]], DataImputed$imputations[[5]])

<<http://www.mattblackwell.org>http://www.mattblackwell.org>http://www .mattblackwell.orgÃ‚

> >On Wed, Nov 11, 2015 at 1:14 AM, W. D.

<<mailto:WD@a7h.com><mailto:WD@a7h.com>WD@a7h.com> wrote:

<<http://lists.gking.harvard.edu/?info=amelia>http://lists.gking.harva rd.edu/?info=amelia>http://lists.gking.harvard.edu/?info=amelia

>More info about Amelia:

<<http://gking.harvard.edu/amelia>http://gking.harvard.edu/amelia>http ://gking.harvard.edu/amelia >>Amelia mailing list >><mailto:Amelia@lists.gking.harvard.edu><mailto:Amelia@lists.gking.ha>

rvard.edu>Amelia(a)lists.gking.harvard.edu

> >To unsubscribe from this list or get other information: > ><<https://lists.gking.harvard.edu/mailman/listinfo/amelia>https://li

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Honaker, James

18 Nov 18 Nov

1:27 a.m.

New subject: Example for ameliabind?

Following on Ista's comment, if you wanted to do this in Zelig, the newest version 5 on CRAN is now pretty seamless with Amelia output. In your example for linear regression it would be: library(Amelia) library(Zelig) DataImputed <- amelia(x=GroupData,incheck=TRUE) Zelig.out <- zelig(DepVar ~ IndVar1 + IndVar2 + IndVar3 + IndVar4 + IndVar5, model="ls", data=DataImputed) summary(Zelig.out) Notice, you just pass Amelia output to the data argument in Zelig, as if it was a dataset (it is really just a very complicated dataset object, with lots of other useful things in there). Zelig recognizes it's an imputed dataset, runs the model on each, and then combines the results. You can see some further details on the zeligproject.org site here: http://docs.zeligproject.org/en/latest/using-Zelig-with-Amelia.html Zelig is under very active development, and if you see any problems, or have suggestions, or things aren't obvious, do please let me know. In fact there are changes in the Beta version of Zelig (version 5.0-8) for summarizing and plotting with imputed datasets, that aren't yet on CRAN (version 5.0-7), so I might suggest you give the Beta a shot. You can install from our repository as: install.packages("Zelig", type="source", repos="http://r.iq.harvard.edu/") Best, James -- James Honaker, Senior Research Scientist //// Institute for Quantitative Social Science, Harvard University ________________________________ From: amelia-bounces(a)lists.gking.harvard.edu [amelia-bounces(a)lists.gking.harvard.edu] on behalf of Ista Zahn [istazahn(a)gmail.com] Sent: Saturday, November 14, 2015 5:14 PM To: W. D. Cc: amelia(a)lists.gking.harvard.edu Subject: Re: [amelia] Example for ameliabind? It doesn't make sense statistically to fit models to the combined data like that. Instead you should fit your model separately to each imputed dataset and then aggregate the estimates and standard errors across the model fits. There are R packages that will do this for you, see e.g., Zelig and mitools packages and section 4.10 in the Amelia package vignette. Best, Ista On Nov 14, 2015 3:29 PM, "W. D." <WD@a7h.com<mailto:WD@a7h.com>> wrote: At 22:40 11/12/2015, W. D. wrote:

...

At 21:30 11/12/2015, Matt Blackwell wrote:

Hi there,Â I actually don't think you actually need to use ameliabind() here.

The amelia output already has all of the datasets together. It might help us to know what is it that you want to accomplish with ameliabind() in this case.

Cheers, Matt

Thanks, Matt. I'm just trying to do a plain old linear regression.

...

On Thu, Nov 12, 2015 at 10:11 PM, W. D. <<mailto:WD@a7h.com<mailto:WD@a7h.com>>WD@a7h.com<mailto:WD@a7h.com>> wrote: At 06:47 11/11/2015, Matt Blackwell wrote: >Hi there,Ã‚ > >The 5 imputed datasets are actually contained in the DataImputed

object and you can access each imputed dataset like so:

> >DataImputed$imputations[[1]] >DataImputed$imputations[[2]] > >And so on. ameliabind() will merge the output of two amelia() calls

into 1 so that if each had 5 imputed datasets, then the binded object will have 10.Ã‚

Thanks for the clue, Matt. However when I run: DataImputedAll <- ameliabind(DataImputed$imputations[[1]],

DataImputed$imputations[[2]], DataImputed$imputations[[3]], DataImputed$imputations[[4]], DataImputed$imputations[[5]])

<<http://www.mattblackwell.org<https://urldefense.proofpoint.com/v2/url?u=http-3A__www.mattblackwell.org&d=CwMFaQ&c=WO-RGvefibhHBZq3fL85hQ&r=vKy-EsvURsbv0l2INFeCgRyXqzbaAyEFxuMtgYHVEpo&m=ARD-CRyJMFMm33TLIIFik4d8eLugb8Uqhrjf2bo5TB4&s=eXW2PPwk59E6x0Nd1dQkgdFkJwJaWpA-1DYqidfSMac&e=>>http://www.mattblackwell.org<https://urldefense.proofpoint.com/v2/url?u=http-3A__www.mattblackwell.org&d=CwMFaQ&c=WO-RGvefibhHBZq3fL85hQ&r=vKy-EsvURsbv0l2INFeCgRyXqzbaAyEFxuMtgYHVEpo&m=ARD-CRyJMFMm33TLIIFik4d8eLugb8Uqhrjf2bo5TB4&s=eXW2PPwk59E6x0Nd1dQkgdFkJwJaWpA-1DYqidfSMac&e=>>http://www<https://urldefense.proofpoint.com/v2/url?u=http-3A__www&d=CwMFaQ&c=WO-RGvefibhHBZq3fL85hQ&r=vKy-EsvURsbv0l2INFeCgRyXqzbaAyEFxuMtgYHVEpo&m=ARD-CRyJMFMm33TLIIFik4d8eLugb8Uqhrjf2bo5TB4&s=-Du6TT8LOfmvMTZ8o13WP_gWc2xYamy_Zrnjjm_hf4A&e=> .mattblackwell.orgÃ‚

> >On Wed, Nov 11, 2015 at 1:14 AM, W. D.

<<mailto:WD@a7h.com<mailto:WD@a7h.com>><mailto:WD@a7h.com<mailto:WD@a7h.com>>WD@a7h.com<mailto:WD@a7h.com>> wrote:

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Skip Barbour

6:46 a.m.

New subject: Example for ameliabind?

If you have used AmeliView how would those datasets be combined in Zelig ? On Wednesday, November 18, 2015, Honaker, James <jhonaker(a)iq.harvard.edu> wrote:

...

Following on Ista's comment, if you wanted to do this in Zelig, the newest version 5 on CRAN is now pretty seamless with Amelia output. In your example for linear regression it would be: library(Amelia) library(Zelig) DataImputed <- amelia(x=GroupData,incheck=TRUE) Zelig.out <- zelig(DepVar ~ IndVar1 + IndVar2 + IndVar3 + IndVar4 + IndVar5, model="ls", data=DataImputed) summary(Zelig.out) Notice, you just pass Amelia output to the data argument in Zelig, as if it was a dataset (it is really just a very complicated dataset object, with lots of other useful things in there). Zelig recognizes it's an imputed dataset, runs the model on each, and then combines the results. You can see some further details on the zeligproject.org site here: http://docs.zeligproject.org/en/latest/using-Zelig-with-Amelia.html Zelig is under very active development, and if you see any problems, or have suggestions, or things aren't obvious, do please let me know. In fact there are changes in the Beta version of Zelig (version 5.0-8) for summarizing and plotting with imputed datasets, that aren't yet on CRAN (version 5.0-7), so I might suggest you give the Beta a shot. You can install from our repository as: install.packages("Zelig", type="source", repos="http://r.iq.harvard.edu/") Best, James -- James Honaker, Senior Research Scientist //// Institute for Quantitative Social Science, Harvard University ------------------------------ *From:* amelia-bounces(a)lists.gking.harvard.edu <javascript:_e(%7B%7D,'cvml','amelia-bounces@lists.gking.harvard.edu');> [ amelia-bounces(a)lists.gking.harvard.edu <javascript:_e(%7B%7D,'cvml','amelia-bounces@lists.gking.harvard.edu');>] on behalf of Ista Zahn [istazahn(a)gmail.com <javascript:_e(%7B%7D,'cvml','istazahn@gmail.com');>] *Sent:* Saturday, November 14, 2015 5:14 PM *To:* W. D. *Cc:* amelia(a)lists.gking.harvard.edu <javascript:_e(%7B%7D,'cvml','amelia@lists.gking.harvard.edu');> *Subject:* Re: [amelia] Example for ameliabind? It doesn't make sense statistically to fit models to the combined data like that. Instead you should fit your model separately to each imputed dataset and then aggregate the estimates and standard errors across the model fits. There are R packages that will do this for you, see e.g., Zelig and mitools packages and section 4.10 in the Amelia package vignette. Best, Ista On Nov 14, 2015 3:29 PM, "W. D." <WD(a)a7h.com <javascript:_e(%7B%7D,'cvml','WD@a7h.com');>> wrote:

At 22:40 11/12/2015, W. D. wrote:

At 21:30 11/12/2015, Matt Blackwell wrote:

Hi there,Â I actually don't think you actually need to use ameliabind() here.

The amelia output already has all of the datasets together. It might help us to know what is it that you want to accomplish with ameliabind() in this case.

Cheers, Matt

Thanks, Matt. I'm just trying to do a plain old linear regression.

<javascript:_e(%7B%7D,'cvml','WD@a7h.com');>>WD@a7h.com <javascript:_e(%7B%7D,'cvml','WD@a7h.com');>> wrote:

At 06:47 11/11/2015, Matt Blackwell wrote: >Hi there,Ã‚ > >The 5 imputed datasets are actually contained in the DataImputed

object and you can access each imputed dataset like so:

> >DataImputed$imputations[[1]] >DataImputed$imputations[[2]] > >And so on. ameliabind() will merge the output of two amelia() calls

into 1 so that if each had 5 imputed datasets, then the binded object will have 10.Ã‚

Thanks for the clue, Matt. However when I run: DataImputedAll <- ameliabind(DataImputed$imputations[[1]],

DataImputed$imputations[[2]], DataImputed$imputations[[3]], DataImputed$imputations[[4]], DataImputed$imputations[[5]])

<<http://www.mattblackwell.org

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.mattblackwell.orgÃ‚

> >On Wed, Nov 11, 2015 at 1:14 AM, W. D.

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Skip Barbour

6:49 a.m.

New subject: Example for ameliabind?

I use AmeliaView due to the ease of setting bounds to avoid unrealistic values. On Wednesday, November 18, 2015, Skip Barbour <russellbarbour(a)gmail.com> wrote:

...

If you have used AmeliView how would those datasets be combined in Zelig ? On Wednesday, November 18, 2015, Honaker, James <jhonaker(a)iq.harvard.edu <javascript:_e(%7B%7D,'cvml','jhonaker@iq.harvard.edu');>> wrote:

Following on Ista's comment, if you wanted to do this in Zelig, the newest version 5 on CRAN is now pretty seamless with Amelia output. In your example for linear regression it would be: library(Amelia) library(Zelig) DataImputed <- amelia(x=GroupData,incheck=TRUE) Zelig.out <- zelig(DepVar ~ IndVar1 + IndVar2 + IndVar3 + IndVar4 + IndVar5, model="ls", data=DataImputed) summary(Zelig.out) Notice, you just pass Amelia output to the data argument in Zelig, as if it was a dataset (it is really just a very complicated dataset object, with lots of other useful things in there). Zelig recognizes it's an imputed dataset, runs the model on each, and then combines the results. You can see some further details on the zeligproject.org site here: http://docs.zeligproject.org/en/latest/using-Zelig-with-Amelia.html Zelig is under very active development, and if you see any problems, or have suggestions, or things aren't obvious, do please let me know. In fact there are changes in the Beta version of Zelig (version 5.0-8) for summarizing and plotting with imputed datasets, that aren't yet on CRAN (version 5.0-7), so I might suggest you give the Beta a shot. You can install from our repository as: install.packages("Zelig", type="source", repos="http://r.iq.harvard.edu/ ") Best, James -- James Honaker, Senior Research Scientist //// Institute for Quantitative Social Science, Harvard University ------------------------------ *From:* amelia-bounces(a)lists.gking.harvard.edu [ amelia-bounces(a)lists.gking.harvard.edu] on behalf of Ista Zahn [ istazahn(a)gmail.com] *Sent:* Saturday, November 14, 2015 5:14 PM *To:* W. D. *Cc:* amelia(a)lists.gking.harvard.edu *Subject:* Re: [amelia] Example for ameliabind? It doesn't make sense statistically to fit models to the combined data like that. Instead you should fit your model separately to each imputed dataset and then aggregate the estimates and standard errors across the model fits. There are R packages that will do this for you, see e.g., Zelig and mitools packages and section 4.10 in the Amelia package vignette. Best, Ista On Nov 14, 2015 3:29 PM, "W. D." <WD(a)a7h.com> wrote:

At 22:40 11/12/2015, W. D. wrote:

At 21:30 11/12/2015, Matt Blackwell wrote: >Hi there,Â > >I actually don't think you actually need to use ameliabind() here. The amelia output already has all of the datasets together. It might help us to know what is it that you want to accomplish with ameliabind() in this case. > >Cheers, >Matt Thanks, Matt. I'm just trying to do a plain old linear regression.

wrote:

>At 06:47 11/11/2015, Matt Blackwell wrote: >>Hi there,Ã‚ >> >>The 5 imputed datasets are actually contained in the DataImputed object and you can access each imputed dataset like so: >> >>DataImputed$imputations[[1]] >>DataImputed$imputations[[2]] >> >>And so on. ameliabind() will merge the output of two amelia() calls into 1 so that if each had 5 imputed datasets, then the binded object will have 10.Ã‚ > >Thanks for the clue, Matt. > >However when I run: > >DataImputedAll <- ameliabind(DataImputed$imputations[[1]], DataImputed$imputations[[2]], DataImputed$imputations[[3]], DataImputed$imputations[[4]], DataImputed$imputations[[5]]) > >It rudely spits out: > > >"All arguments must be amelia output." > >When searching for that particular error, there isn't anything >useful. > >What do you suggest? > >Thanks for your assistance! > > > > >>Hope that helps! >> >>Cheers, >>Matt >> >>~~~~~~~~~~~ >>Matthew Blackwell >>Assistant Professor of Government >>Harvard University >>url: <<http://www.mattblackwell.org

http://www.mattblackwell.org

http://www

.mattblackwell.orgÃ‚ >> >>On Wed, Nov 11, 2015 at 1:14 AM, W. D. <<mailto:WD@a7h.com><mailto:WD@a7h.com>WD@a7h.com> wrote: >>If 5 sets of data are generated using a command like >>this: >> >>DataImputed <- amelia(x=GroupData,incheck=TRUE) >> >>What would be the names of the 5 sets of data in order >>to use ameliabind? >> >>DataImputedAll <- ameliabind(set1?, set2?, set3?, set4?, set5?) >> >>There seem to be a dearth of examples online. >> >>Thanks for your help. >> >>-- >>Amelia mailing list served by HUIT >>[Un]Subscribe/View Archive: <<http://lists.gking.harvard.edu/?info=amelia>http://lists.gking.harva

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Honaker, James
Ista Zahn
Skip Barbour
W. D.