Re: [R] equivalent of stata command in R‏

From: Joris Meys <jorismeys_at_gmail.com>
Date: Wed, 09 Jun 2010 12:40:42 +0200

plm does not have a predict function, so forget my former mail. To get to the coefficients, you just :
coef(mdl)

The rest of the calculations you can figure out I guess.

I'm also not sure if you're doing what you think you're doing. You never specified the index stno in your pml call. Read the help files again. And while you're at it, read the posting guide for the list as well:
http://www.R-project.org/posting-guide.html

Cheers
Joris

On Wed, Jun 9, 2010 at 11:54 AM, mike mick <saint-filth_at_hotmail.com> wrote:
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> From: saint-filth@hotmail.com
> To: saint-filth_at_hotmail.com
> Subject: RE:
> Date: Wed, 9 Jun 2010 09:53:20 +0000
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> OK! sorry thats my fault,
>
> here the translations of the stata commands
> 1st step is to get the mean values of the variables, well that doesnt need explanation i guess,
>
> 2nd step is to estimate the model on panel data estimation method
> which is:
> mdl<-plm(lnLP~lnC+lnL+lnM+lnE+Eco+Inno+Eco*Inno+Eco*lnM+Eco*lnE+year,data=newdata,model="within")
> and basically i need to get the marginal effect of variable "Eco" at the sample mean (step 3) but i am not that good in R so any additional help is wlcome!
> Thanks
> From: saint-filth_at_hotmail.com
> To: r-help_at_r-project.org
> Subject:
> Date: Wed, 9 Jun 2010 09:45:16 +0000
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> It helps if you translate the Stata commands. Not everybody is fluent
> in those. It would even help more if you would enlight us about the
> function you used to fit the model. Getting the marginal effects is
> not that hard at all, but how depends a bit on the function you used
> to estimate the model.
>
> You can try
> predict(your_model,type="terms",terms="the_term_you're_interested_in")
>
> For exact information, look at the respective predict function, eg if
> you use lme, do ?predict.lme
> Be aware of the fact that R normally choses the correct predict
> function without you having to specify it. predict() works for most
> model objects. Yet, depending on the model eacht predict function can
> have different options or different functionality. That information is
> in the help files of the specific function.
>
> Cheers
> Joris
>
> Dear all,
>
> I need to use R for one estimation, and i have readily available stata command, but i need also the R version of the same command.
> the estimation in stata is as following:
> 1. Compute mean values of relevant variables
>
>
>
> . sum inno lnE lnM
>
>
>
> Variable | Obs Mean Std. Dev. Min Max
>
> -------------+--------------------------------------------------------
>
> inno | 146574 .0880374 .2833503 0 1
>
> lnE | 146353 .9256239 1.732912 -4.473922 10.51298
>
> lnM | 146209 4.281903 1.862192 -4.847253 13.71969
>
>
>
> 2. Estimate model
>
>
>
> . xi: xtreg lnLP lnC lnL lnE lnM eco inno eco_inno eco_lnE eco_lnM i.year, fe i(stno)
>
> i.year _Iyear_1997-1999 (naturally coded; _Iyear_1997 omitted)
>
>
>
> Fixed-effects (within) regression Number of obs = 146167
>
> Group variable (i): stno Number of groups = 48855
>
>
>
> R-sq: within = 0.9908 Obs per group: min = 1
>
> between = 0.9122 avg = 3.0
>
> overall = 0.9635 max = 3
>
>
>
> F(11,97301) = 949024.29
>
> corr(u_i, Xb) = 0.2166 Prob > F = 0.0000
>
>
>
> ------------------------------------------------------------------------------
>
> lnLP | Coef. Std. Err. t P>|t| [95% Conf. Interval]
>
> -------------+----------------------------------------------------------------
>
> lnC | .0304896 .0009509 32.06 0.000 .0286258 .0323533
>
> lnL | -.9835998 .0006899 -1425.74 0.000 -.984952 -.9822476
>
> lnE | .0652658 .0009439 69.14 0.000 .0634158 .0671159
>
> lnM | .6729931 .0012158 553.53 0.000 .67061 .6753761
>
> eco | .0610348 .0177048 3.45 0.001 .0263336 .095736
>
> inno | .0173824 .0058224 2.99 0.003 .0059706 .0287943
>
> eco_inno | .0080325 .0110815 0.72 0.469 -.0136872 .0297522
>
> eco_lnE | .0276226 .004059 6.81 0.000 .019667 .0355781
>
> eco_lnM | -.0214237 .0039927 -5.37 0.000 -.0292494 -.0135981
>
> _Iyear_1998 | -.0317684 .0013978 -22.73 0.000 -.034508 -.0290287
>
> _Iyear_1999 | -.0647261 .0027674 -23.39 0.000 -.0701501 -.0593021
>
> _cons | 1.802112 .009304 193.69 0.000 1.783876 1.820348
>
> -------------+----------------------------------------------------------------
>
> sigma_u | .38142386
>
> sigma_e | .2173114
>
> rho | .75494455 (fraction of variance due to u_i)
>
> ------------------------------------------------------------------------------
>
> F test that all u_i=0: F(48854, 97301) = 3.30 Prob > F = 0.0000
>
>
>
> 3. Compute marginal effect of eco at sample mean
>
>
>
> . nlcom (_b[eco]+_b[inno]*.0880374+_b[eco_lnE]*.9256239+_b[eco_lnM]*4.281903)
>
>
>
> _nl_1: _b[eco]+_b[inno]*.0880374+_b[eco_lnE]*.9256239+_b[eco_lnM]*4.281903
>
>
>
> ------------------------------------------------------------------------------
>
> lnLP | Coef. Std. Err. t P>|t| [95% Conf. Interval]
>
> -------------+----------------------------------------------------------------
>
> _nl_1 | -.0036011 .008167 -0.44 0.659 -.0196084 .0124061
>
> ------------------------------------------------------------------------------
>
>
>
> in fact i can find the mean of the variables ( step 1) and extimate the model (step 2) but i couldnt find the equivalent of step 3 (compute marginal effect of eco at sample mean). Can someone help me for this issue?
>
> Cheers!
> Windows 7: Size en uygun bilgisayar bulun. Daha fazla bilgi edinin.
> _________________________________________________________________
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>
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>
>

-- 
Joris Meys
Statistical consultant

Ghent University
Faculty of Bioscience Engineering
Department of Applied mathematics, biometrics and process control

tel : +32 9 264 59 87
Joris.Meys_at_Ugent.be
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Received on Wed 09 Jun 2010 - 12:05:51 GMT

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