I'm trying to migrate a tobit model from Stata to R.
The Stata commands for robust would be to just add ,vce(robust)
to the model. And for clustering it would be ,vce(cluster idvar)
.
Reproducible Stata example:
use http://www.ats.ucla.edu/stat/stata/dae/tobit, clear
tobit apt read math i.prog, ul(800)
tobit apt read math i.prog, ul(800) vce(cluster prog)
Reproducible R example:
library("VGAM")
dat <- read.csv("http://www.ats.ucla.edu/stat/data/tobit.csv")
summary(m <- vglm(apt ~ read + math + prog, tobit(Upper = 800), data = dat))
My understanding is that coeftest(m, vcov = sandwich)
should give me robust se.
But I get the following: Error: $ operator not defined for this S4 class.
Could someone suggest an approach for estimating the robust se from the vglm model and also clustered se with vglm?
After spending a whole day looking into this question myself, I think I finally found an appropriate package: Zelig
.
http://docs.zeligproject.org/en/latest/zelig-tobit.html
Compare without clustering to clustering:
WITHOUT
> summary(m <- zelig(apt ~ read + math + prog,
below=0, above=Inf, model="tobit", data = dat))
How to cite this model in Zelig:
Kosuke Imai, Gary King, and Olivia Lau. 2015.
"tobit: Linear regression for Left-Censored Dependent Variable"
in Kosuke Imai, Gary King, and Olivia Lau, "Zelig: Everyone's Statistical Software,"
http://gking.harvard.edu/zelig
Call:
"survreg"(formula = formula, dist = "gaussian", data = data,
robust = robust)
Value Std. Error z p
(Intercept) 242.74 29.760 8.16 3.45e-16
read 2.55 0.576 4.43 9.24e-06
math 5.38 0.651 8.27 1.31e-16
proggeneral -13.74 11.596 -1.18 2.36e-01
progvocational -48.83 12.818 -3.81 1.39e-04
Log(scale) 4.12 0.050 82.41 0.00e+00
Scale= 61.6
Gaussian distribution
Loglik(model)= -1107.9 Loglik(intercept only)= -1202.8
Chisq= 189.72 on 4 degrees of freedom, p= 0
Number of Newton-Raphson Iterations: 5
n= 200
WITH
> summary(m <- zelig(apt ~ read + math + prog, below=0,
above=Inf, model="tobit",
data = dat,robust=T,cluster="prog"))
How to cite this model in Zelig:
Kosuke Imai, Gary King, and Olivia Lau. 2015.
"tobit: Linear regression for Left-Censored Dependent Variable"
in Kosuke Imai, Gary King, and Olivia Lau, "Zelig: Everyone's Statistical Software,"
http://gking.harvard.edu/zelig
Call:
"survreg"(formula = formula, dist = "gaussian", data = data,
robust = robust)
Value Std. Err (Naive SE) z p
(Intercept) 242.74 2.8315 29.760 85.73 0.00e+00
read 2.55 0.3159 0.576 8.08 6.40e-16
math 5.38 0.2770 0.651 19.44 3.78e-84
proggeneral -13.74 0.3252 11.596 -42.25 0.00e+00
progvocational -48.83 0.1978 12.818 -246.83 0.00e+00
Log(scale) 4.12 0.0586 0.050 70.34 0.00e+00
Scale= 61.6
Gaussian distribution
Loglik(model)= -1107.9 Loglik(intercept only)= -1202.8
Chisq= 189.72 on 4 degrees of freedom, p= 0
(Loglikelihood assumes independent observations)
Number of Newton-Raphson Iterations: 5
n= 200
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