Clarify

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by bughunterfeb＠gmail.com

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2 years, 7 months

Changes to Clarify list

by Mukerjee, Zagreb

Hello users of Clarify, We are moving the discussion of this mailing list to our Github. For discussing Clarify, asking questions, or suggesting features, please use our Github discussions, found at https://github.com/iqss-research/clarify/discussions. To report any bugs, please fill out this form: https://github.com/iqss-research/<https://github.com/iqss-research/relogit/issues/new>clarify<https://github.com/iqss-research/clarify/discussions>/issues/new<https://github.com/iqss-research/relogit/issues/new>. Thank you, Zagreb Mukerjee Research Data Scientist IQSS

2 years, 11 months

Re: [clarify] question on using estsimp with mi() and FE

by Gary King

Hi Julia, if you are having troubles, the easiest thing to do would be to run Clarify separately on each of the Amelia imputed data sets and to combine the results afterwards. Best of luck with your research, Gary -- *Gary King* - Albert J. Weatherhead III University Professor - Director, IQSS <http://iq.harvard.edu/> - Harvard University GaryKing.org - King(a)Harvard.edu - @KingGary <https://twitter.com/kinggary> - 617-500-7570 - Assistant <king-assist(a)iq.harvard.edu>: 617-495-9271 On Mon, Sep 25, 2017 at 3:21 AM, Julia CAGE <julia.cage(a)sciencespo.fr> wrote: > Hi all, > > I have an issue with the combined use of Clarify/Amelia and I don't know > how to solve it. > > Basically, I am estimating a sureg model for electoral data with district > and election FE. > > If I run the following model, everything works well: > > xi : estsimp sureg (lvotesP1 controls i.yearst i.district) > (lvotesP2 controls i.yearst i.district) > (lvotesP3 controls i.yearst i.district), sims(1000) > > However, as soon as I add the mi() option (I multiply imputed the missing > voting data and I want to use the information from all the datasets) then I > got an error message linked to the FE (I have no problem when no FE are not > included): > > variable _Iyearst_2 not found > > (and I cannot enter the FE manually because Stata only supports a limited > number of variables) > > Note that this is not linked to my yearst variable; if I only use the > district FE, I got the same error message but for _Idistrict_2 > > Could you please let me know what I should do to fix this issue? > > Thanks! > Best, > Julia > > -------------------------------------------- > Julia Cagé > Assistant Professor of Economics > Sciences Po Paris, Department of Economics > https://sites.google.com/site/juliacagehomepage/ > Email: julia.cage(a)sciencespo.fr >

6 years, 7 months

question on using estsimp with mi() and FE

by Julia CAGE

Hi all, I have an issue with the combined use of Clarify/Amelia and I don't know how to solve it. Basically, I am estimating a sureg model for electoral data with district and election FE. If I run the following model, everything works well: xi : estsimp sureg (lvotesP1 controls i.yearst i.district) (lvotesP2 controls i.yearst i.district) (lvotesP3 controls i.yearst i.district), sims(1000) However, as soon as I add the mi() option (I multiply imputed the missing voting data and I want to use the information from all the datasets) then I got an error message linked to the FE (I have no problem when no FE are not included): variable _Iyearst_2 not found (and I cannot enter the FE manually because Stata only supports a limited number of variables) Note that this is not linked to my yearst variable; if I only use the district FE, I got the same error message but for _Idistrict_2 Could you please let me know what I should do to fix this issue? Thanks! Best, Julia -------------------------------------------- Julia Cagé Assistant Professor of Economics Sciences Po Paris, Department of Economics https://sites.google.com/site/juliacagehomepage/ Email: julia.cage(a)sciencespo.fr

6 years, 7 months

Problems saving changes in predicted probabilities with CLARIFY

by Barbet Porta, Berta

Dear all, My name is Berta Barbet and I am a PhD Student at the University of Leicester, United Kingdom. I am trying to analyse whether or not the impact of different issues at explaining voters decision changes through time in several countries. In order to do so I am performing several MNL regressions with issue positions as IV and vote as DV. And now I would like to plot the results into graph to make the visualisation of the importance of the different issues more clear. I was using the prchange command for the SPost package. But this package does not offer confidence intervals for the predicted values, so I decided to use the CLARIFY package. However, I have not managed to find a way to save these results with this package and I have not been able to find anyone who can help me. So far I have manage to calculate the changes in predicted values using: estsimp mlogit vote Welfare Defense Constitutionalism Decentralization European_Integration Morality Freedom Multiculturalism Labour Market Green if year==1992 setx mean simqi, fd(prval(1 2 3 5)) changex(Defense min max) genpr(defense92_1 defense92_2 defense92_3 defense92_5) Although I would prefer to calculate the change in predicted values by moving one SD above and below the mean, instead of min-max, in general the results that show in the screen are enough. However, I cannot save them. esttab commands do not work with the package. And the package only seems to save monte carlo simulations for the predicted values not for anything different. I have thought about the possibility of calculating the predicted probabilities at the different points and then just compute the difference and their variances. The problem is that unless I find a way to estimate the predicted probability at the highest and lowest value together, something that I have not been able to do (I only know who to do it by asking it to estimate them separated), the values of the Monte Carlo simulations saved come from different simulations. Hence, I should not substract them because they are not comparable. I have a lot of results, so saving them manually would imply a lot of work and risks making mistakes. Thank you very much for your help and patience. Kind regards, Berta Barbet Porta

9 years, 1 month

Clarify - nbreg and simulated alpha

by Javier Marquez

I noted that Clarify's -nbreg- routine simulates alpha (the dispersion parameter) by simulating ln(alpha) and then exponentiating each draw. However, the results (predicted values) are different if one simulates directly from alpha. Is the first method preferable than the latter? Thanks in advance. Kind regads, Javier

10 years, 8 months

Clarify with xtpcse models

by Ping Xu

Dear all, Does anyone know how to use clarify estsimp command with xtpcse models? I saw that people used estsimp_pcse command, but I simply could not get it work in my Stata 12. Any suggestions? Thanks, Ping

10 years, 9 months

clarify, amelia and xtreg

by Jenifer Whitten-Woodring

Hi, I am trying to use Clarify to analyze some imputed data from Amelia. The problem is that my preliminary analyses indicate I need to use xtreg and Clarify doesn't appear to support this model. Any suggestions? Thanks, Jenifer -- Jenifer Whitten-Woodring, PhD Assistant Professor University of Massachusetts Lowell Department of Political Science 978-934-4242 jenifer_whittenwoodring(a)uml.edu

11 years, 8 months

first difference test in models with interaction effects

by Oshrat Hochman

Hi all, if you want to test for first difference in an interaction model (logistic regression) of the following sort: y=a+b1x1+b2x2+b3x1x3 where both x1 and x2 are dummy variables you would normally write: simqi , prval(1) fd(prval(1)) changex(x1 0 1). Right? but would the program than know for itself that when x1==0 the interaction effect x1x2 is also 0? can one take a significant difference to be indicative or does the model not make any sense? or is there an alternative command for this situation? Thanks in advance, a sociologist -- Oshrat Hochman, PhD Department of Sociology and Anthropology Tel Aviv University

12 years

Estimating level changes

by Thomas Didier

Dear Clarify users, I have a question. Is there a way with CLARIFY to calculate the impact of a change in the LEVEL of an explanatory variable (X) on the LEVEL of the dependent variable(Y)? With OLS, the way to do it is simply to make the following calculation: Delta Y = b Delta X, where b is the unstandardized regression coefficient (Achen 1982). With logistic regression, the above formula is inappropriate. Possible solutions are: (1) To use weighted least-squares or generalized least-squares (Finkel, JoP, 1993: 8). In this case, the regression coefficient can be used directly to estimate the impact of a change in the LEVEL of X on the change in the LEVEL of Y. (2) To use the (quite demanding) approach proposed by Denk and Finkel in the 1992 AJPS piece. Could Clarify perform a similar estimation with logistic regressions? Many thanks for your help, Thomas Didier McGill University

12 years

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