On this R-data statistics page, you will find information about the RepVict data set which pertains to Repeat Victimization Data. The RepVict data set is found in the vcd R package. You can load the RepVict data set in R by issuing the following command at the console data("RepVict"). This will load the data into a variable called RepVict. If R says the RepVict data set is not found, you can try installing the package by issuing this command install.packages("vcd") and then attempt to reload the data. If you need to download R, you can go to the R project website. You can download a CSV (comma separated values) version of the RepVict R data set. The size of this file is about 439 bytes.

Repeat Victimization Data

Description

Data from Reiss (1980) given by Fienberg (1980) about instances of repeat victimization for households in the U.S. National Crime Survey.

Usage

data("RepVict")

Format

A 2-dimensional array resulting from cross-tabulating victimization. The variables and their levels are as follows:

R project statistics dataset table

No	Name	Levels
1	First Victimization	Rape, Assault, Robbery, Pickpocket, Personal Larceny,
		Burglary, Household Larceny, Auto Theft
2	Second Victimization	Rape, Assault, Robbery, Pickpocket, Personal Larceny,
		Burglary, Household Larceny, Auto Theft

Source

Michael Friendly (2000), Visualizing Categorical Data, page 113.

References

S. E. Fienberg (1980), The Analysis of Cross-Classified Categorical Data, MIT Press, Cambridge, 2nd edition.

A. J. J. Reiss (1980), Victim proneness by type of crime in repeat victimization. In S. E. Fienberg & A. J. J. Reiss (eds.), Indicators of Crime and Criminal Justice. U.S. Government Printing Office, Washington, DC.

M. Friendly (2000), Visualizing Categorical Data. SAS Institute, Cary, NC.

Examples

data("RepVict")mosaic(RepVict[-c(4,7),-c(4,7)], gp = shading_max,
       main = "Repeat Victimization Data")

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Dataset imported from https://www.r-project.org.