
Show HN: ciTools – Quickly calculate uncertainty intervals in R - jth0
https://github.com/jthaman/ciTools
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confounded
This is promising, I very frequently end up writing one off functions to munge
data on CIs between lme4 and ggplot2.

However, what a prediction interval _actually means_ is a slightly conentuous
issue in the context of mixed models, and Douglas Bates had plenty of caution
about constructing/interpreting them on the R mailing lists a few years back.

This said, I’ve always found the tip-toeing around constructing them annoying;
it just means that there’s little standard practice.

Do you have any documentation on how you’re doing prediction intervals for
mixed models, and what interpretations do and don’t make sense for your
method?

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jth0
Good question! There is a vignette in the GitHub version that specifically
addresses mixed models and lists exactly which variances and standard errors
are incorporated in interval estimation. We show in the vignette that our
intervals reach the nominal coverage level asymptotically.

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confounded
Fantastic!

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minimaxir
I'm confused by the use of ggplot2 as shown in the example: ggplot2 and
geom_smooth() already calculates and plots confidence intervals by default.
What does this package add to a ggplot?

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jth0
ciTools doesn't add anything to ggplot, it creates tidy dataframes that are
easy to plot with ggplot. In the example, we show CIs and PIs on a linear
mixed model, which ggplot can't handle.

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crumpke
Hmmm, nothing to do with continuous integration?

