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

In BinaryEPPM: Mean and Variance Modeling of Binary Data

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")

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]

Source

Rousseeuw P, Croux C, Todorov V, Ruckstuhl A, Salibian-Barrera M, Verbeke T, Koller M, Maechler M (2016).robustbase: Basic Robust Statistics. R package version 0.92-6, http://robustbase.r-forge.r-project.org/.

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. doi: 10.1080/01621459.1989.10478791.

Examples

data(foodstamp.grouped)

BinaryEPPM documentation built on July 31, 2019, 5:08 p.m.