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  • $\begingroup$ Thank you for your answer. As a matter of fact, I've seen someone using a series of binary contrasts indeed, but with a "general estimating equation". How does that relate to the methods you mentioned? Moreover, when making several comparisons, don't you need to correct for the multiple comparison problem? $\endgroup$ Commented Oct 6, 2016 at 6:07
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    $\begingroup$ Another way to estimate a mixed effects model with ordinal response in R is via the mixor function of the mixor package. This function allows for random slopes and intercepts and provides some choice over the link function (you are not restricted to ordered logistic regression but can also use the probit, log-log, and complementary log-log link functions). $\endgroup$ Commented Jul 30, 2019 at 20:36
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    $\begingroup$ Want to come back and add a worked example? $\endgroup$ Commented Oct 28, 2019 at 0:11
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    $\begingroup$ it's probably harder than I want it to be ... $\endgroup$ Commented Oct 28, 2019 at 1:13
  • $\begingroup$ I've had some convergence problems with mixor. Bayesian random effects ordinal models tend to behave better in my limited experience. $\endgroup$ Commented Jul 15, 2023 at 11:32