Thanx for your response,
yeah, i know i didnst specified the indexes
when i wrote the 2nd mail, in fact in the 1st mail i wrote already that
i dont have problem with the estimation of the model... thats the
reason why i didnt write in fact since the issue is not to estimate the
model but to get the marginal effect,
anyway, i figured out that predict(), doesnt work for panel data...
and
well, my problem is that contrary to your guess, i couldnt figure out
the rest of the calculations... since i am not that experienced in R.
one last help of yours would be quite helpful to get rid of this silly problem!
Thanx again...
> Date: Wed, 9 Jun 2010 12:40:42 +0200
> Subject: Re: [R] equivalent of stata command in R
> From: jorismeys@gmail.com
> To: saint-filth@hotmail.com
> CC: r-help@r-project.org
>
> 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@hotmail.com>
wrote:
> >
> >
> >
> >
> >
> >
> >
> >
> > From: saint-filth@hotmail.com
> > To: saint-filth@hotmail.com
> > Subject: RE:
> > Date: Wed, 9 Jun 2010 09:53:20 +0000
> >
> >
> >
> >
> >
> >
> >
> >
> >
> > 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@hotmail.com
> > To: r-help@r-project.org
> > Subject:
> > Date: Wed, 9 Jun 2010 09:45:16 +0000
> >
> >
> >
> >
> >
> >
> >
> > 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!
> >
> >
> >
> > ______________________________________________
> > R-help@r-project.org mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> > and provide commented, minimal, self-contained, reproducible code.
> >
> >
>
>
>
> --
> 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@Ugent.be
> -------------------------------
> Disclaimer : http://helpdesk.ugent.be/e-maildisclaimer.php
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