As of now likert is available as separate package.

This will produce two separate panels, but it fits on a single page. Plot.likert(resp.array, layout=c(2,1), main='') Resp.array <- t(apply(subset(resp, grp='B'), 2, table))ĭimnames(resp.array) <- list(NULL, NULL, group=levels(grp)) Resp.array <- t(apply(subset(resp, grp='A'), 2, table)) # compute responses frequencies separately by grp To use a grouping variable, you'll need to work with an array of numerical values. RightAxisLabels=NULL, rightAxis=NULL, ylab.right='', So let's start again with fresh (counts) statistics: plot.likert(t(apply(resp, 2, table)), main='', as.percent=TRUE, Plot.likert(resp.likert$results*82/100, main='')īut that will complicate things a bit because we need to convert frequencies to counts, subset the likert object produced by irutils, detach package, etc. We could reuse the above code as shown below: resp.likert <- likert(resp) I would like to draw your attention on another package, HH, that allows to plot Likert scales as diverging stacked barcharts. (Those are ggplot2 objects, but you won't be able to arrange them on a single page with gridExtra::grid.arrange() because of readability issue!) You can probably process them afterwards. E.g., using 12 items, plot(likert(resp, grouping=grp)) I would thus suggest to reduce your dataset to smaller subsets of items. It works without grouping (e.g., plot(likert(resp))), though. That should just work, but the visual rendering will be awful because of the high number of items. Resp.likert <- likert(resp, grouping=grp) Grp <- gl(2, 82/2, labels=LETTERS) # say equal group size for simplicity Resp <- ame(lapply(resp, factor, ordered=TRUE, # Simulate some data (82 respondents x 66 items) Then, with R, try the following: library(irutils) On my Mac, I did % tar -czf jbryer-irutils-0573195 Then you can install the package the way you are used to do on your machine. by replacing all occurrences of likert$items with likert$items. Second, there's an incorrect instruction to fetch items labels, where a i is dangling around line 175. First, in likert, cast() is used but the reshape package is never loaded (although there's an import(reshape) instruction in the NAMESPACE file). You'll need to hack the R/likert.R file, specifically the likert and plot.likert functions. Start by downloading a zipped version from Github. I came across this package some months ago.Īs of commit 0573195c07 on Github, the code won't work with a grouping= argument. If you really want to use stacked barcharts with such a large number of items, here are two possible solutions.

Convert spss code to r