5.13: Summary of important R code

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5.13 Summary of important R code

The main components of R code used in this chapter follow with components to modify in lighter and/or ALL CAPS text where y is a response variable and x is a predictor are easily identified:

TABLENAME <- tally(~ x + y, data = DATASETNAME)
- This function requires that the mosaic package has been loaded.
- This provides a table of the counts in the variable called TABLENAME.
- margins = T is used if you want to display row, column, and table totals.
plot(y ~ x, data = DATASETNAME)
- Makes a stacked bar chart useful for homogeneity test situations.
mosaicplot(TABLENAME)
- Makes a mosaic plot useful for finding patterns in the table in independence test situations.
tableplot(data = DATASETNAME, sortCol = VARIABLENAME, pals = list(“BrBG”))
- Makes a tableplot sorted by VARIABLENAME, requires that the tabplot and RColorBrewer packages have been loaded.
- The pals = list("BrBG") option provides a color-blind friendly color palette, although other options are possible, such as pals = list("RdBu").
chisq.test(TABLENAME)
- Provides $X^2$ and p-values based on the $\boldsymbol{\chi^2}$-distribution with $(R-1)(C-1)$ degrees of freedom.
chisq.test(TABLENAME)$expected
- Provides expected cell counts.
pchisq(X-SQUARED, df = (R - 1)*(C - 1), lower.tail = F)
- Provides p-value from $\boldsymbol{\chi^2}$-distribution with $(R-1)(C-1)$ degrees of freedom for observed test statistic.
- See Section 5.5 for code related to finding a permutation-based p-value.
chisq.test(TABLENAME)$residuals^2
- Provides $X^2$ contributions from each cell in table.
chisq.test(TABLENAME)$residuals
- Provides standardized residuals.
mosaicplot(TABLENAME, shade = T)
- Provides a mosaic plot with shading based on standardized residuals.

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