On this R-data statistics page, you will find information about the PreSex data set which pertains to Pre-marital Sex and Divorce. The PreSex data set is found in the vcd R package. You can load the PreSex data set in R by issuing the following command at the console data("PreSex"). This will load the data into a variable called PreSex. If R says the PreSex 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 PreSex R data set. The size of this file is about 570 bytes.

Pre-marital Sex and Divorce

Description

Data from Thornes \& Collard (1979), reported in Gilbert (1981), on pre- and extra-marital sex and divorce.

Usage

data("PreSex")

Format

A 4-dimensional array resulting from cross-tabulating 1036 observations on 4 variables. The variables and their levels are as follows:

R project statistics dataset table

No	Name	Levels
1	MaritalStatus	Divorced, Married
2	ExtramaritalSex	Yes, No
3	PremaritalSex	Yes, No
4	Gender	Women, Men

Source

Michael Friendly (2000), Visualizing Categorical Data: http://euclid.psych.yorku.ca/ftp/sas/vcd/catdata/marital.sas

References

G. N. Gilbert (1981), Modelling Society: An Introduction to Loglinear Analysis for Social Researchers. Allen and Unwin, London.

B. Thornes \& J. Collard (1979), Who Divorces?. Routledge \& Kegan, London.

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

Examples

data("PreSex")## Mosaic display for Gender and Premarital Sexual Experience
## (Gender Pre)
mosaic(margin.table(PreSex, c(3,4)), 
                main = "Gender and Premarital Sex")## (Gender Pre)(Extra)
mosaic(margin.table(PreSex, c(2,3,4)), 
       expected = ~Gender * PremaritalSex + ExtramaritalSex ,
           main = "PreMaritalSex*Gender +Sex")## (Gender Pre Extra)(Marital)
mosaic(PreSex,
       expected = ~Gender*PremaritalSex*ExtramaritalSex + MaritalStatus,
       main = "PreMarital*ExtraMarital + MaritalStatus")## (GPE)(PEM)
mosaic(PreSex, 
       expected = ~ Gender * PremaritalSex * ExtramaritalSex
                    + MaritalStatus * PremaritalSex * ExtramaritalSex,
       main = "G*P*E + P*E*M")

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