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 Râ > From: jorism...@gmail.com > To: saint-fi...@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-fi...@hotmail.com> wrote: > > > > > > > > > > > > > > > > > > From: saint-fi...@hotmail.com > > To: saint-fi...@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-fi...@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.m...@ugent.be > ------------------------------- > Disclaimer : http://helpdesk.ugent.be/e-maildisclaimer.php > _________________________________________________________________ Yeni Windows 7: Gündelik iÅlerinizi basitleÅtirin. Size en uygun bilgisayarı bulun. http://windows.microsoft.com/shop [[alternative HTML version deleted]]
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