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 arent
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 isnt correct, because standard errors are so small.
Thank you for the help,
Roberta Niquini.
--
ENSP - Fiocruz
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