# Dyke: Sources of Knowledge of Cancer In vcdExtra: 'vcd' Extensions and Additions

 Dyke R Documentation

## Sources of Knowledge of Cancer

### Description

Observational data on a sample of 1729 individuals, cross-classified in a 2^5 table according to their sources of information (read newspapers, listen to the radio, do 'solid' reading, attend lectures) and whether they have good or poor knowledge regarding cancer. Knowledge of cancer is often treated as the response.

data(Dyke)

### Format

A 5-dimensional array resulting from cross-tabulating 5 variables for 1729 observations. The variable names and their levels are:

 No Name Levels 1 Knowledge "Good", "Poor" 2 Reading "No", "Yes" 3 Radio "No", "Yes" 4 Lectures "No", "Yes" 5 Newspaper "No", "Yes"

### Source

Fienberg, S. E. (1980). The Analysis of Cross-Classified Categorical Data Cambridge, MA: MIT Press, p. 85, Table 5-6.

### References

Dyke, G. V. and Patterson, H. D. (1952). Analysis of factorial arrangements when the data are proportions. Biometrics, 8, 1-12.

Lindsey, J. K. (1993). Models for Repeated Measurements Oxford, UK: Oxford University Press, p. 57.

### Examples

data(Dyke)

# independence model

# null model, Knowledge as response, independent of others
require(MASS)
dyke.mod0 <- loglm(~ Knowledge + (Reading * Radio * Lectures * Newspaper), data=Dyke)
dyke.mod0
mosaic(dyke.mod0)

# view as doubledecker plot
Dyke <- Dyke[2:1,,,,]    # make Good the highlighted value of Knowledge
doubledecker(Knowledge ~ ., data=Dyke)
# better version, with some options
margins = c(1,6, length(dim(Dyke)) + 1, 1),
fill_boxes=list(rep(c("white", gray(.90)),4))
)

# separate (conditional) plots for those who attend lectures and those who do not
main="Do not attend lectures",
margins = c(1,6, length(dim(Dyke)) + 1, 1),
fill_boxes=list(rep(c("white", gray(.90)),3))
)