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ivdesign: Hypothesis Testing in Cluster-Randomized Encouragement Designs
An implementation of randomization-based hypothesis testing for three different estimands in a cluster-randomized encouragement experiment. The three estimands include (1) testing a cluster-level constant proportional treatment effect (Fisher's sharp null hypothesis), (2) pooled effect ratio, and (3) average cluster effect ratio. To test the third estimand, user needs to install 'Gurobi' (>= 9.0.1) optimizer via its R API. Please refer to <https://www.gurobi.com/documentation/9.0/refman/ins_the_r_package.html>.
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Package details |
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| Author | Bo Zhang |
| Maintainer | Bo Zhang <bozhan@wharton.upenn.edu> |
| License | GPL-3 |
| Version | 0.1.0 |
| Package repository | View on CRAN |
| Installation |
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