I'm looking for some critiquing on a technique that I've been using to display a particular type of survey question. I came to it due to a frustration of existing methods used in the market research industry (not least the common technique of calculating means for ordinal data).
A Likert scale is a symmetrical scale to assess a statement. Usually the scale would be 5 point though 7 would be sensible to use, especially if you're expecting a narrow distribution of results (usually mostly positive or negative). The scale is usually something like 'strongly disagree, disagree, neutral, agree, strongly agree'.
I've written a long note on my site here
. Summarizing, I took that the viewer wanted to understand 3 elements:
skew - the balance between positive and negative responses
non-neutrality - the proportion of respondents who had either a positive or negative view
Strength of feelings - the split between agree and strongly agree.
Histograms are good at showing the distribution of small numbers of distributions, however I felt their weakness was that you could either arrange so the response-types were aligned or the proportions were aligned, but not both.
Stacked distributions are widely used but these suffer from comparing non-extreme values due to differing bases. Here is an example:
My 'net stacked distribution' tries to counter this. Here is the the same data:
As you can see I've rebased the responses to a central, and have excluded the neutral responses. The neutral can be inferred as inversely proportional to the length of the overall bar.
As noted, I'm looking for a critique. My nagging worry is that I've missed something & there is a good reason few others are using this approach.