Modelo térmico de elementos concentrados

A multi-level structure is very common in many experiments. While incorporating random effects into quantile regression, there are a few approaches. A Bayesian approach was used in this paper exploiting the properties of the Asymmetric Laplace Distribution (ALD). Using the ALD’s decomposition in to a mixture of a normal and an exponential random variable, we are able to incorporate random effects into the model. We used this model formulation to address the impact of an education intervention from a randomized controlled trial. The study had several known sources of variation. We considered a two-level model (student and school) in order to evaluate the effect of the intervention on student’s critical thinking abilities. The results showed that there was a significant positive benefit from exposure to the intervention for low scoring students (small quantiles) while there was no benefit from the intervention for high scoring students. This result suggests that the intervention may have the ability to help bring the bottom up without widening inequality in student performance in our schools.

The main contribution was the result from the application that showed the effect of the intervention on critical thinking scores was substantial for low scoring students which non- significant for high scoring students. Further work would attempt to improve estimation of more than two-levels. Other work could evaluate the impact of the intervention on other subgroups of students.

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