I am trying to fit a rank-ordered logit model using brms and am running into some trouble. This type of model is used when respondents are asked to give the full rank of their preferences among all considered options. To begin solving this problem I first used a frequentist approach as a sanity che…

As a follow up, I’m still looking for help with this problem. Any assistance from anyone on the forum would be greatly appreciated!!

This won’t answer your question precisely, but you might want to look at the example brms syntax in this thread: https://github.com/paul-buerkner/brms/issues/560 re: the “fishing” dataset from the mlogit package. Even though the data structure differs, the brms syntax work well for discrete choice m…

Thank you for responding to my question. I have tried the brms syntax on the thread you suggested and I still can’t get the parameter estimates to roughly correspond to the frequentist estimates I get from the mlogit package. I’ve also tried syntax from some other threads but they didn’t work. Thus…

Can you post the updated model code you are using?

I’m basically using code like @paul.buerkner used in the github link earlier in this thread: library(brms) # choice data in **wide** format data("Fishing", package = "mlogit") Fishing$noboat <- 0 # the first 50 persons did not have the "boat" option Fishing$noboat[1:50] <- -100 bform2 <- bf( mo…

The other possibility is that I’m on the wrong track entirely. There just seems like there has to be a more rich way to analyze a rank order of a list from each participant than modeling their top choice. For example, if someone ranks their favorite colors as being blue, green, red, and then yellow,…

For this kind of data, I recommend ordinal models, which have rich support in brms. I have also written a paper about this topic in case you are interested: https://psyarxiv.com/x8swp/

Interesting. Though I got the sense from the paper (which seems great by the way) that ordinal models are only applicable when an outcome variable is both categorical and has natural orderings. I’m interested in how to model where people fully rank a variable like color where the levels don’t have a…

I see. In such a case, models such as the Thurstonian IRT model may be more appropriate, but I am not enough into the details of your question to be able to tell exactly. Some basic Thurstonian IRT models can be fitted with my thurstonianIRT package ( https://github.com/paul-buerkner/thurstonianIRT ) …

I was interested in the rank ordered logit model because for each respondent I have their ranking of the response options of a categorical variable with no natural ordering. This is very common in marketing. For example, data video game console preference might show that a respondent’s first prefere…

Rank-ordered logit model in brms

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paul.buerkner May 1, 2020, 1:26pm 12

I understand. This is something that would imply modeling all pairwise comparisons between options as done, for example, in the Thurstonian IRT model, or generalizations of it.

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Rank-ordered logit model in brms

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