Food Stamp Program Participation
This data consists of 150 randomly selected persons from a survey with information on over 2000 elderly US citizens, where the response, indicates participation in the U.S. Food Stamp Program.
data(foodstamp, package="robustbase")
A data frame with 150 observations on the following 4 variables.
participationparticipation in U.S. Food Stamp Program; yes = 1, no = 0
tenancytenancy, indicating home ownership; yes = 1, no = 0
suppl.incomesupplemental income, indicating whether some form of supplemental security income is received; yes = 1, no = 0
incomemonthly income (in US dollars)
Data description and first analysis: Stefanski et al.(1986) who indicate Rizek(1978) as original source of the larger study.
Electronic version from CRAN package catdata.
Rizek, R. L. (1978) The 1977-78 Nationwide Food Consumption Survey. Family Econ. Rev., Fall, 3–7.
Stefanski, L. A., Carroll, R. J. and Ruppert, D. (1986) Optimally bounded score functions for generalized linear models with applications to logistic regression. Biometrika 73, 413–424.
Künsch, H. R., Stefanski, L. A., Carroll, R. J. (1989) Conditionally unbiased bounded-influence estimation in general regression models, with applications to generalized linear models. J. American Statistical Association 84, 460–466.
data(foodstamp)
(T123 <- xtabs(~ participation+ tenancy+ suppl.income, data=foodstamp))
summary(T123) ## ==> the binary var's are clearly not independent
foodSt <- within(foodstamp, {
logInc <- log(1 + income)
rm(income)
})
m1 <- glm(participation ~ ., family=binomial, data=foodSt)
summary(m1)
rm1 <- glmrob(participation ~ ., family=binomial, data=foodSt)
summary(rm1)
## Now use robust weights.on.x :
rm2 <- glmrob(participation ~ ., family=binomial, data=foodSt,
weights.on.x = "robCov")
summary(rm2)## aha, now the weights are different:
which( weights(rm2, type="robust") < 0.5)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.