5.13: Summary of important R code
- Page ID
- 33261
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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.
- This function requires that the
- 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
andRColorBrewer
packages have been loaded. - The
pals = list("BrBG")
option provides a color-blind friendly color palette, although other options are possible, such aspals = list("RdBu")
.
- Makes a tableplot sorted by VARIABLENAME, requires that the
- 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.