  School value-added models are widely applied to study, monitor, and hold
schools to account for school differences in student learning. The traditional
model is a mixed-effects linear regression of student current achievement on
student prior achievement, background characteristics, and a school random
intercept effect. The latter is referred to as the school value-added score and
measures the mean student covariate-adjusted achievement in each school. In
this article, we argue that further insights may be gained by additionally
studying the variance in this quantity in each school. These include the
ability to identify both individual schools and school types that exhibit
unusually high or low variability in student achievement, even after accounting
for differences in student intakes. We explore and illustrate how this can be
done via fitting mixed-effects location scale versions of the traditional
school value-added model. We discuss the implications of our work for research
and school accountability systems.
