foodstamp.grouped: Participation in the federal food stamp program as a list not a data frame.

Description

The dependent variable is a list of frequency distributions of binary variables indicating participation in the federal food stamp program. The independent variables are two binary ones i.e., tenancy and supplemental income, and a continuous one of the log(monthly income+1).

Usage

data("foodstamp.grouped")

Arguments

Format

The format is: List of 5 $ l.participation:List of 150 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 0 1 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 0 1 ..$ : num [1:2] 1 0 ..$ : num [1:2] 0 1 ..$ : num [1:2] 1 0 ..$ : num [1:2] 0 1 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 0 1 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 0 1 ..$ : num [1:2] 0 1 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 0 1 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 0 1 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 0 1 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 0 1 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 0 1 ..$ : num [1:2] 0 1 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 .. [list output truncated] $ tenancy : Factor w/ 2 levels "0","1": 2 2 2 2 1 2 2 2 1 2 ... $ suppl.income : Factor w/ 2 levels "0","1": 1 1 2 1 1 1 1 1 1 1 ... $ income : int [1:150] 271 287 714 521 0 518 458 1266 350 168 ... $ l.weights1 :List of 150 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 0 1 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 0 0.656 ..$ : num [1:2] 1 0 ..$ : num [1:2] 0 1 ..$ : num [1:2] 1 0 ..$ : num [1:2] 0 1 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 0 0.441 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 0 1 ..$ : num [1:2] 0 1 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 0 1 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 0 0.127 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 0 1 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 0 0.647 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 0 1 ..$ : num [1:2] 0 0.556 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 ..$ : num [1:2] 1 0 .. [list output truncated]

References

Kunsch HR, Stefanski LA, Carroll RJ (1989). Conditionally Unbiased Bounded-Influence Estimation in General Regression Models, with Applications to Generalized Linear Models. Journal of the American Statistical Association, 84(406), 460-466. 10.1080/01621459.1989.10478791.

Examples

Run this code

# NOT RUN {
data(foodstamp.grouped)
# }

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