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Last Published October 25, 2021 01:46 PM November 01, 2021 06:29 PM
Primary Outcomes (Explanation) The primary form of missing data will be follow-up tests that are not taken. Our main approach will be to code these tests as “not negative” rather than “missing”. This lumps together missing and positive tests (a common approach in the literature). However, we will show the relationship between treatment assignment and test taking and utilize bounding exercises (e.g. Lee bounds) to clearly demonstrate the range of potential impacts missing data could be having on our results. This applies to all test results, both contingent and follow-up.
Secondary Outcomes (End Points) We will assess differences between the control group and incentive groups (pooled), as well as between the control group and the most effective incentive group (or incentive combination), as chosen by the “smart pooling and pruning method”, in the following secondary outcomes: - Duration of time in treatment program - Earnings - Employment (dummy) - Medical care utilization o ED visits o Inpatient stays o Primary care utilization - Total cost of care We will assess differences between the control group and incentive groups (pooled), as well as between the control group and the most effective incentive group (or incentive combination), as chosen by the “smart pooling and pruning method”, in the following secondary outcomes: - Duration of time in treatment program - Earnings - Employment (dummy) - Medical care utilization o ED visits o Inpatient stays o Primary care utilization - Total cost of care - Incentive amount per negative follow-up test (i.e., “cost-effectiveness”)
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