Microsoft Technology Licensing, LLC

Nanyu Chen

Ya Xu

Weitao Duan

Bryan G Ng

The disclosed embodiments provide a system for evaluating a performance of a mobile application. During operation, the system obtains a first set of data associated with adopters of a new version of a mobile application in a partial rollout of the new version and a second set of data associated with non-adopters of the new version in the partial rollout. Next, the system applies a statistical model to the first and second sets of data to select a subset of the non-adopters as potential adopters of the new version. The system then reduces a bias in a quasi-experimental design associated with the mobile application by using the first set of data and a third set of data associated with the potential adopters to estimate an average treatment effect (ATE) between the new version and an older version of the mobile application.

Model-based matching for removing selection bias in quasi-experimental testing of mobile applications

The disclosed embodiments provide a system for evaluating a performance of a mobile application. During operation, the system obtains, for a statistical model used in a quasi-experimental design, a first predicted outcome produced from a first set of data that is collected from two substantially identical versions of a mobile application. Next, the system uses the first predicted outcome to assess a bias of the statistical model. The system then improves an accuracy of the statistical model by using the assessed bias to normalize a second predicted outcome of the statistical model.

Growing community of inventors

Sunnyvale, CA, United States of America

Nanyu Chen