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I'm trying to fit a linear quantile mixed model with multiple group variables for random effects.

With lme4 in R, I can use model <- lmer(target ~ feat1 + (1|feat2) + (1|feat3), data) which gets me two set of random effects for both feat2 and feat3.

Is it possible to do anything similar for quantile models? Reading through the doc for lqmm, it seems it can only do one group variable?

Woody
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    Is your question about the stats methods of building this model, or the code? If stats, it should be moved to [stats.se]; if it's code, it's fine here. Either way it needs a [reproducible example](https://stackoverflow.com/q/5963269/5325862) – camille Feb 08 '23 at 01:45
  • Agree wit suggestion to migrate; this appears to be a package recommendation request. You have found a package that does not meet your needs and you want advice about other packages that might satisfy them. Time for the stats experts at https://stats.stackexchange.com/ . You definitely need to explain the reasons for this effort and the research question more expansively. – IRTFM Feb 08 '23 at 02:17
  • I'm actually asking if there's an existing package that can achieve this. If not, I can try to move this to the other sites. Thanks! – Woody Feb 10 '23 at 01:52

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