Using Quantile Regression to draw relational inference between conditional quantiles and explanatory predictors

A principal investigator wants to build quantile regression models that draw statistical inference about the relationship between the conditional quantiles (lower quartile,median, upper quartile) of medical expenditure and the explanatory predictors including age, health status, and supplementary insurance. Although not necessary, the medical expenditure is log-transformed (which might also be valid for an ordinary linear regression by comparison).

This information is collected in meps1.sav. See the topic Sample Files for more information.

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