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## Panel-data interval regression with random coefficients

### What's this about?

Suppose you have panel data and want to fit a random-effects model to an interval-measured outcome such as income bracket or age group.

If ylower and yupper record the upper and lower endpoints of the outcome, we could type

  . xtset id
. xtintreg ylower yupper x1 x2 x3


to fit a model with random intercepts by id. The xtintreg command is not new, but the meintreg command is. You can fit the same model with meintreg by typing

  . meintreg ylower yupper x1 x2 x3 || id:


The advantage of using meintreg is that it does not restrict us to random intercepts. What if the coefficient for x1 varies across the levels of id? We can fit a random-coefficients model by typing

  . meintreg ylower yupper x1 x2 x3 || id: x1


You can see an example and learn more about the new meintreg command. That example fits a model with city-level random intercepts,

  . meintreg exerlo exerup age work kids walk || cid:


The model could easily be extended to allow for random coefficients on age and work by typing

  . meintreg exerlo exerup age work kids walk || cid: age work


### Highlights

• Interval-measured outcomes, including
• Interval-censored
• Left-censored
• Right-censored
• Random effects
• Random intercepts
• Random coefficients
• Graphs of marginal means and marginal effects
• Intraclass correlation
• Support for complex survey data
• Support for Bayesian estimation

### Tell me more

You can also fit Bayesian panel-data (multilevel) interval regression using the bayes prefix.

Learn more about Stata's panel-data features.

Read more about multilevel interval regression in the Stata Multilevel Mixed-Effects Reference Manual; see [ME] meintreg.