Hi,
I would like to estimate coefficients using poisson regression and then get
standard errors that are adjusted for heteroskedasticity, using a complex
sample survey data. Then I will calculate prevalence ratio and confidence
intervals.
Can sandwich estimator of variance be used when observations aren?t
independent? In my case, observations are independent across groups
(clusters), but not necessarily within groups. Can I calculate the standard
errors with robust variance, in complex sample survey data using R?
Outputs:
design_tarv<-svydesign(ids=~X2, strata=~X3, data=banco, weights=~X4)
banco.glm7 <- svyglm(y ~x1, data = banco, family = poisson (link= "log"),
design= design_tarv)
summary(banco.glm7)
Call:
svyglm(y ~ x1, data = banco, family = poisson(link = "log"),
design = design_tarv)
Survey design:
svydesign(ids = ~X2, strata = ~X3, data = banco,
weights = ~X4)
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.91893 0.04696 -19.570 < 2e-16 ***
x1 0.19710 0.06568 3.001 0.00603 **
---
Signif. codes: 0 ?***? 0.001 ?**? 0.01 ?*? 0.05 ?.? 0.1 ? ? 1
(Dispersion parameter for poisson family taken to be 0.5722583)
Number of Fisher Scoring iterations: 5
library(sandwich)
vcovHC(banco.glm7)
(Intercept) x1
(Intercept) 4.806945e-13 -4.771409e-13
x1 -4.771409e-13 7.127168e-13
sqrt(diag(vcovHC(banco.glm7, type="HC0")))
(Intercept) x1
6.923295e-07 8.426314e-07
# I think this result isn?t correct, because standard errors are so small.
Thank you for the help,
Roberta Niquini.
--
ENSP - Fiocruz
svyglm and sandwich estimator of variance
2 messages · Roberta Pereira Niquini, Thomas Lumley
3 days later
On Fri, 19 Dec 2008, Roberta Pereira Niquini wrote:
Hi, I would like to estimate coefficients using poisson regression and then get standard errors that are adjusted for heteroskedasticity, using a complex sample survey data. Then I will calculate prevalence ratio and confidence intervals. Can sandwich estimator of variance be used when observations aren?t independent? In my case, observations are independent across groups (clusters), but not necessarily within groups. Can I calculate the standard errors with robust variance, in complex sample survey data using R?
The standard errors that svyglm() produces are already the sandwich estimator and already correctly handle the clustering. Use vcov() to extract the variance-covariance matrix, if you need it, or SE() to extract the standard errors. -thomas
Outputs:
design_tarv<-svydesign(ids=~X2, strata=~X3, data=banco, weights=~X4)
banco.glm7 <- svyglm(y ~x1, data = banco, family = poisson (link= "log"),
design= design_tarv)
summary(banco.glm7)
Call:
svyglm(y ~ x1, data = banco, family = poisson(link = "log"),
design = design_tarv)
Survey design:
svydesign(ids = ~X2, strata = ~X3, data = banco,
weights = ~X4)
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.91893 0.04696 -19.570 < 2e-16 ***
x1 0.19710 0.06568 3.001 0.00603 **
---
Signif. codes: 0 ?***? 0.001 ?**? 0.01 ?*? 0.05 ?.? 0.1 ? ? 1
(Dispersion parameter for poisson family taken to be 0.5722583)
Number of Fisher Scoring iterations: 5
library(sandwich)
vcovHC(banco.glm7)
(Intercept) x1
(Intercept) 4.806945e-13 -4.771409e-13
x1 -4.771409e-13 7.127168e-13
sqrt(diag(vcovHC(banco.glm7, type="HC0")))
(Intercept) x1
6.923295e-07 8.426314e-07
# I think this result isn?t correct, because standard errors are so small.
Thank you for the help,
Roberta Niquini.
--
ENSP - Fiocruz
______________________________________________ R-help at 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.
Thomas Lumley Assoc. Professor, Biostatistics tlumley at u.washington.edu University of Washington, Seattle