Thank you for considering my email and replying.
Well, I am working with TIMSS 2007 survey data ( Trends in
international mathematics and science study).
TIMSS is a stratified DATA, where the primary sampling unit is the
school
I want to test the effect of some independent variables reflecting the
socio-economic status of students on math achievement
I have 18 independent variables :Female+Age+calculator+computer+desk+
dictionary+internet+work+Book2+Book3+Book4+Book5+Pedu1+Pedu2+Pedu3+Pedu4+Born1+Born2
All my variables are binary variables except for age, and of course the
dependent variable wich is the achievement score of the student (Math1
in my regression)
I have a sample of 3169 observations (i.e students, 3169 achievement
scores)
Data is missing at 23%.
The idea is to test the effect of these variables (known to reflect the
socio-economic status of students) at the lower and upper quantiles
taking into account the survey design features (sampling weight (which
is in my case the studnt weight) clustering and stratification)
Why do I need th psudo-R squared? Because I want to calculate the
increase in the pseudo r squared after introducing the school variales:
I explain
I will do first regressions with the socio-economic variables (SES), and
I calculate the pseudo R squared
In a second stage, I will introduce the school variables ( which are
also binary variables), after controlling for socio-economic status, and
calculate the pseudo R squared. The difference between the two pseudo R
squared will tell me if SES variables account more or less than school
variables for students' achievement.
Why with replicates? To eliminate the intra-cluster correlations between
schools.
I ran the following commands successfully:
mydesign
<-svydesign(ids=~IDSCHOOL,strata=~IDSTRATE,data=TUN,nest=TRUE,weights=~TOTWGT)
bootdesign <- as.svrepdesign(mydesign,type="auto",replicates=150)
fit<-withReplicates(bootdesign,quote(coef(rq(Math1~Female+Age+calculator+computer+desk+
+dictionary+internet+work+Book2+Book3+Book4+Book5+Pedu1+Pedu2+Pedu3+Pedu4+Born1+Born2,tau=0.9,weights=.weights,
method="fn"))))
I want get the pseudo R squared but I failed. I read a query dating from
August 2006, [R] Pseudo R for Quant Reg and the answer to it:
# from https://stat.ethz.ch/pipermail/r-help/2006-August/110386.html
rho <- function(u,tau=.5)u*(tau - (u < 0))
V <- sum(rho(f$resid, f$tau))
The structure of my fit object is the following:
str (fit)
Class 'svrepstat' atomic [1:19] 713.24 -24.01 -18.37 9.05 7.71
...
..- attr(*, "var")= num [1:19, 1:19] 2839.3 10.2 -122.1 -332.4
-42.3
...
.. ..- attr(*, "dimnames")=List of 2
.. .. ..$ : chr [1:19] "(Intercept)" "Female" "Age"
"calculator" ...
.. .. ..$ : chr [1:19] "(Intercept)" "Female" "Age"
"calculator" ...
.. ..- attr(*, "means")= Named num [1:19] 710.97 -24.03 -18.3
9.39
7.58 ...
.. .. ..- attr(*, "names")= chr [1:19] "(Intercept)" "Female"
"Age"
"calculator" ...
..- attr(*, "statistic")= chr "theta"
Thank you in advance for replying and for your help
Le 2014-09-18 18:55, David L Carlson a écrit :
It is hard to say because we do not have enough information. R has
approximately 6,000 packages and you have not told us which ones you
are using. You have not told us much about your data and you have not
told us where to find the query from August 2006. The basic problem is
that your "fit" is not the same as the "f" in the query. Your fit
object is not very complicated. If you look at the output from
str(fit) you will see that fit is an "atomic" vector (note the wording
in your error message) with a series of attributes that are probably
documented in the help pages for the functions you are using. There is
nothing called resid inside fit. It is likely that the post you are
looking at refers to the output from rq(...) or perhaps
predict(rq(...)), but not the output from withReplicates(...,
quote(coef(rq(...)))) which is what fit is.
-------------------------------------
David L Carlson
Department of Anthropology
Texas A&M University
College Station, TX 77840-4352
-----Original Message-----
From: r-help-boun...@r-project.org
[mailto:r-help-boun...@r-project.org] On Behalf Of Donia Smaali
Bouhlila
Sent: Thursday, September 18, 2014 9:54 AM
To: r-help@r-project.org
Subject: [R] Pseudo R squared for quantile regression with replicates
Hi,
I am a new user of r software. I intend to do quantile regressions with
complex survey data using replicate method. I have ran the following
commands successfully:
mydesign
<-svydesign(ids=~IDSCHOOL,strata=~IDSTRATE,data=TUN,nest=TRUE,weights=~TOTWGT)
bootdesign <- as.svrepdesign(mydesign,type="auto",replicates=150)
fit<-
withReplicates(bootdesign,quote(coef(rq(Math1~Female+Age+calculator+computer+desk+
+
dictionary+internet+work+Book2+Book3+Book4+Book5+Pedu1+Pedu2+Pedu3+Pedu4+Born1+Born2,tau=0.5,weights=.weights,
method="fn"))))
I want get the pseudo R squared but I failed. I read a query dating
from
August 2006, [R] Pseudo R for Quant Reg and the answer to it:
rho <- function(u,tau=.5)u*(tau - (u < 0))
V <- sum(rho(f$resid, f$tau))
I copied it and paste it , replacing f by fit I get this error
message:
Error in fit$resid : $ operator is invalid for atomic vectors, I don't
know what it means
The fit object is likely to be quite complicated I used str() to see
what it looks like:
str (fit)
Class 'svrepstat' atomic [1:19] 713.24 -24.01 -18.37 9.05 7.71 ...
..- attr(*, "var")= num [1:19, 1:19] 2839.3 10.2 -122.1 -332.4 -42.3
...
.. ..- attr(*, "dimnames")=List of 2
.. .. ..$ : chr [1:19] "(Intercept)" "Female" "Age" "calculator" ...
.. .. ..$ : chr [1:19] "(Intercept)" "Female" "Age" "calculator" ...
.. ..- attr(*, "means")= Named num [1:19] 710.97 -24.03 -18.3 9.39
7.58 ...
.. .. ..- attr(*, "names")= chr [1:19] "(Intercept)" "Female" "Age"
"calculator" ...
..- attr(*, "statistic")= chr "theta"
How can I retrieve the residuals?? and calculate the pseudo R squared??
Any help please
--
Dr. Donia Smaali Bouhlila
Associate-Professor
Department of Economics
Faculté des Sciences Economiques et de Gestion de Tunis
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