Explore >> Select a destination


You are here

brunomioto.com
| | juliasilge.com
3.3 parsecs away

Travel
| | A data science blog
| | r4ds.had.co.nz
5.4 parsecs away

Travel
| | You're reading the first edition of R4DS; for the latest on this topic see the Communication chapter in the second edition. 28.1 Introduction In \[exploratory data analysis\], you learned how to...
| | statsandr.com
2.9 parsecs away

Travel
| | Learn how to create professional graphics and plots in R (histogram, barplot, boxplot, scatter plot, line plot, density plot, etc.) with the ggplot2 package
| | www.rdatagen.net
32.4 parsecs away

Travel
| I was thinking a lot about proportional-odds cumulative logit models last fall while designing a study to evaluate an intervention's effect on meat consumption. After a fairly extensive pilot study, we had determined that participants can have quite a difficult time recalling precise quantities of meat consumption, so we were forced to move to a categorical response. (This was somewhat unfortunate, because we would not have continuous or even count outcomes, and as a result, might not be able to pick up small changes in behavior.) We opted for a question that was based on 30-day meat consumption: none, 1-3 times per month, 1 time per week, etc. - six groups in total. The question was how best to evaluate effectiveness of the intervention?