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zevross.com | ||
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timogrossenbacher.ch
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| | | | | In this blog post, I show how to easily produce a categorical spatial interpolation from a set of georeferenced points - only using the tidyverse, sf and the package kknn. | |
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r4ds.had.co.nz
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| | | | | 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... | |
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tech.popdata.org
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| | | | | Remotely sensed precipitation data can provide important context for understanding the health outcomes reported in the DHS | |
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www.rdatagen.net
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| | | 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? | ||
