Combining synthetic controls and interrupted time series analysis to improve causal inference in program evaluation


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DOI 10.1111/jep.12882
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References found in this work BETA

Using Machine Learning to Assess Covariate Balance in Matching Studies.Ariel Linden & Paul R. Yarnold - 2016 - Journal of Evaluation in Clinical Practice 22 (6):848-854.
A Matching Framework to Improve Causal Inference in Interrupted Time-Series Analysis.Ariel Linden - 2018 - Journal of Evaluation in Clinical Practice 24 (2):408-415.

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Citations of this work BETA

Using Permutation Tests to Enhance Causal Inference in Interrupted Time Series Analysis.Ariel Linden - 2018 - Journal of Evaluation in Clinical Practice 24 (3):496-501.

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A Matching Framework to Improve Causal Inference in Interrupted Time-Series Analysis.Ariel Linden - 2018 - Journal of Evaluation in Clinical Practice 24 (2):408-415.
Challenges to Validity in Single‐Group Interrupted Time Series Analysis.Ariel Linden - 2017 - Journal of Evaluation in Clinical Practice 23 (2):413-418.
The Limits of Piecemeal Causal Inference.Conor Mayo-Wilson - 2014 - British Journal for the Philosophy of Science 65 (2):213-249.

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