Your help was everything i needed it. Please, declare this topic as solved. And thanks again.
On Sat, Sep 3, 2016 at 10:06 PM, David Winsemius <dwinsem...@comcast.net> wrote: > > > On Sep 2, 2016, at 6:08 PM, Juan Ceccarelli Arias <jfca...@gmail.com> > wrote: > > > > Thanks a lot. Your code does the trick. > > One last question: > > The tabulate produced is showing every cross in just one column. > > I mean, it presents the region by order and sex=1, and then again the > > region but by sex==2. > > Can i list or present as this: > > sex1 sex2 > > region1 323. 3434.. > > ... > > regionN 123.. 432.. > > > > and ignoring the remaining info (standar errors or se in this case)? > > Again, thanks Anthony. Really. > > > (Anthony's probably asleep.) > > This doesn't ignore the se's but that could be easily done by omitting > that column from the data argument: > > From the examples on the help page for svymean: > > > svyby( ~ mobility , ~ stype + comp.imp , dclus1 , svymean ) > stype comp.imp mobility se > E.No E No 19.71875 1.347583 > H.No H No 13.14286 0.740017 > M.No M No 14.81818 2.960618 > E.Yes E Yes 17.28571 1.536158 > H.Yes H Yes 35.14286 16.570001 > M.Yes M Yes 13.71429 2.628573 > > apimeans1 <- svyby( ~ mobility , ~ stype + comp.imp , dclus1 , svymean ) > > > reshape(apimeans1, idvar='stype', direction="wide", timevar="comp.imp") > stype mobility.No se.No mobility.Yes se.Yes > E.No E 19.71875 1.347583 17.28571 1.536158 > H.No H 13.14286 0.740017 35.14286 16.570001 > M.No M 14.81818 2.960618 13.71429 2.628573 > > -- > David. > > > > > > > > > > > On Fri, Sep 2, 2016 at 8:24 PM, Anthony Damico <ajdam...@gmail.com> > wrote: > > > >> # mean > >> svymean( ~ income_variable , NN ) > >> svyby( ~ income_variable , ~ age + sex , NN , svymean ) > >> > >> # median > >> svyquantile( ~ income_variable , NN ) > >> svyby( ~ income_variable , ~ age + sex , NN , svyquantile , 0.5 ) > >> > >> > >> > >> > >> On Fri, Sep 2, 2016 at 3:04 PM, Juan Ceccarelli Arias < > jfca...@gmail.com> > >> wrote: > >> > >>> Hello > >>> Im analyzing a survey and i need to obtain some statistics per groups. > >>> Im able to create a table with sex and age. However, if i want to know > how > >>> much income earns the population by sex and age, i can't. > >>> Im loading the dataset as describe the line below > >>> NN <- svydesign(ids = ~1, data = encuesta, weights = fact) > >>> Some simple table i can create > >>> table(svytable(~age+sex,design=NN)) > >>> But im not able to handle the same tabulate referencing a income > variable, > >>> in this case, wage. > >>> Can you help me? > >>> Thanks for your replies and time. > >>> > >>> [[alternative HTML version deleted]] > >>> > >>> ______________________________________________ > >>> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > >>> https://stat.ethz.ch/mailman/listinfo/r-help > >>> PLEASE do read the posting guide http://www.R-project.org/posti > >>> ng-guide.html > >>> and provide commented, minimal, self-contained, reproducible code. > >>> > >> > >> > > > > [[alternative HTML version deleted]] > > > > ______________________________________________ > > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > > 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 -- To UNSUBSCRIBE and more, see 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.
