from your stata output, it looks like you need to use the survey package in R
for step-by-step instructions about how to do this (and comparisons to stata), see http://journal.r-project.org/archive/2009-2/RJournal_2009-2_Damico.pdf once you're ready to run the regression, use svyglm() instead of glm() and drop the weights argument (since it will already be part of the survey design) :) On Fri, Nov 23, 2012 at 3:13 PM, Pablo Menese <pmen...@gmail.com> wrote: > Until a weeks ago I used stata for everything. > Now I'm learning R and trying to move. But, in this stage I'm testing R > trying to do the same things than I used to do in stata whit the same > outputs. > I have a problem with the logit, applying weights. > > in stata I have this output > . svy: logit bach job2 mujer i.egp4 programa delay mdeo i.str evprivate > (running logit on estimation sample) > > Survey: Logistic regression > > Number of strata = 1 Number of obs = > 248 > Number of PSUs = 248 Population size = > 5290.1639 > Design df = 247 > F( 11, 237) = 4.39 > Prob > F = 0.0000 > > > Linearized > bach Coef. Std. Err. t P>t [95% Conf. Interval] > > job2 -.4437446 .4385934 -1.01 0.313 -1.307605 .4201154 > mujer 1.070595 .4169919 2.57 0.011 .2492812 1.891908 > > egp4 > 2 -.4839342 .539808 -0.90 0.371 -1.547148 .5792796 > 3 -1.288947 .5347344 -2.41 0.017 -2.342168 -.2357263 > 4 -.8569793 .5106425 -1.68 0.095 -1.862748 .1487898 > > programa .9694352 .5677642 1.71 0.089 -.1488415 2.087712 > delay -1.552582 .5714967 -2.72 0.007 -2.678211 -.426954 > mdeo -.7938904 .3727571 -2.13 0.034 -1.528078 -.0597025 > > str > 2 -1.122691 .5731879 -1.96 0.051 -2.25165 .0062682 > 3 -2.056682 .6350485 -3.24 0.001 -3.307483 -.8058812 > > evprivate -1.962431 .5674143 -3.46 0.001 -3.080018 -.8448431 > _cons 2.308699 .7274924 3.17 0.002 .8758187 3.741578 > > > the best that i get in R was: > > glm(formula = bach ~ job2 + mujer + egp4 + programa + delay + > mdeo + str + evprivate, family = quasibinomial(link = "logit"), > weights = wst7) > > Deviance Residuals: > Min 1Q Median 3Q Max > -12.5951 -3.9034 -0.9412 3.8268 11.2750 > > Coefficients: > Estimate Std. Error t value Pr(>|t|) > (Intercept) 2.3087 0.7173 3.218 0.00147 ** > job2 -0.4437 0.4355 -1.019 0.30926 > mujer 1.0706 0.3558 3.009 0.00290 ** > egp4intermediate (iii, iv) -0.4839 0.4946 -0.978 0.32890 > egp4skilled manual workers -1.2889 0.5268 -2.447 0.01514 * > egp4working class -0.8570 0.4625 -1.853 0.06514 . > programa 0.9694 0.4951 1.958 0.05141 . > delay -1.5526 0.4878 -3.183 0.00166 ** > mdeo -0.7939 0.4207 -1.887 0.06037 . > strest. ii -1.1227 0.4809 -2.334 0.02042 * > strestr. iii -2.0567 0.5134 -4.006 8.28e-05 *** > evprivate -1.9624 0.6490 -3.024 0.00277 ** > --- > Signif. codes: 0 *** 0.001 ** 0.01 * 0.05 . 0.1 1 > > (Dispersion parameter for quasibinomial family taken to be 23.14436) > > Null deviance: 7318.5 on 246 degrees of freedom > Residual deviance: 5692.8 on 235 degrees of freedom > (103 observations deleted due to missingness) > AIC: NA > > Number of Fisher Scoring iterations: 6 > > Warning message: > In summary.glm(logit) : > observations with zero weight not used for calculating dispersion > > this has the same betas but the hypothesis test has differents values... > > > HELP!!!! > > [[alternative HTML version deleted]] > > > ______________________________________________ > 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. > > [[alternative HTML version deleted]]
______________________________________________ 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.
