Improving Generalizations from Experiments: New methods

Improving Generalizations from Experiments: New methods

Recorded on April 4, 2014

Course is aimed at researchers of all levels who are interested in either making generalizations from large-scale experiments that have been completed or planning to conduct large-scale experiments. The course focuses on studies using a cluster randomized or multi-site design including many schools or school districts.

The instructors will introduce methods for improving the external validity of these experiments. The course begins with an overview of the larger issues of generalization, and then provides participants with tools to implement new methods for improving generalizations in their own experimental work. This includes tools for developing a strategic recruitment plan and for improving estimates of the average treatment effect. Participants should be familiar with large-scale experiments.

Topics covered in this course include:

  • Validity and Overview: Review of validity types and approaches to increasing validity.
  • Retrospective Generalizations: Illustrate methods for improving generalization from experiments that have already been conducted.
  • Prospective Methods: Illustrate methods for planning experiments to increase their generalizability to policy relevant populations.


  • Elizabeth Tipton, Teachers College, Columbia University 
  • Larry V. Hedges, Northwestern University



Course No. 108-2014


VRLC Course
Recorded 04/04/2014
Recorded 04/04/2014