[R] Run a fixed effect regression and a logit regression on a national survey that need to be "weighted"

Adams, Jean jvadams at usgs.gov
Tue Sep 20 18:23:45 CEST 2016

If you want your records to be weighted by the survey weights during the
analysis, then use the weights= argument of the glm() function.


On Tue, Sep 20, 2016 at 5:04 AM, laura roncaglia <roncaglia.laura at gmail.com>

> I am a beginner user of R. I am using a national survey to test what
> variables influence the partecipation in complementary pensions (the
> partecipation in complementary pension is voluntary in my country).
> Since the dependent variable is a dummy (1 if the person partecipate and 0
> otherwise) I want to run a logit or probit regression; moreover I want to
> run a fixed effect regression since I subset the survey in order to have
> only the individuals interviewed more than one time.
> The data frame is composed by several social and economical variables and
> it also contain a variable "weight" which is the survey weight (they are
> weighting coefficients to adjust the results of the sample to the national
> data).
>  family pers sex income pension1     10    1   F  10000       12
> 20    1   F  20000       13     20    2   M  40000       04     30
> 1   M  25000       05     30    2   F  50000       06     40    1   M
> 60000       1
> pers is the component of the family and pension takes 1 if the person
> partecipate to complementary pension (it is a semplification of the
> original survey, which contains more variables and observation (aroun 22k
> observations)).
> I know how to use the plm and glm functions for a fixed effect or logit
> regressoin; in this case I don't know what to do since I need to take
> account of the survey weights.
> I used the svydesing function to "weight" the data frame:
> df1 <- svydesign(ids=~1, data=df, weights=~dfweight)
> I used ids=~1 because there isn't a "cluster" variable in the survey (I
> know that the towns are ramdomly selected and then individuals are ramdomly
> selected, but there isn't a variable that indicate the stratification).
> At this point I am lost: I don't know if it is right to use the survey
> package and then what function use to run the regression, or there is a way
> to use the plm or glm functions taking account of the weights.
> I tried so hard to search a solution on the website but if you could give
> me an answer I'd be glad.
>         [[alternative HTML version deleted]]
> ______________________________________________
> R-help at 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]]

More information about the R-help mailing list