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MODEL-BASED MATCHING FOR REMOVING SELECTION BIAS IN QUASI-EXPERIMENTAL TESTING OF MOBILE APPLICATIONS
MODEL-BASED MATCHING FOR REMOVING SELECTION BIAS IN QUASI-EXPERIMENTAL TESTING OF MOBILE APPLICATIONS
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机译:基于模型的移动应用准实验中的选择偏差消除
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摘要
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.
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