Tree-Based Approach for Addressing Self-selection in Impact Studies with Big Data

Professor Galit Shmueli discusses a machine learning algorithm called ‘tree-based approach’ that can be deployed on large and small data sets to overcome problems of self-selection. The tree-based approach can be effectively used to adjust for observable self-selection bias in intervention studies in management research.

Galit Shmueli is Tsing Hua Distinguished Professor at the Institute of Service Science, and Director of the Center for Service Innovation & Analytics at the College of Technology Management, National Tsing Hua University, Taiwan.

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