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  1. Using Group-Based Trajectory Modelling to Enhance Causal Inference in Interrupted Time Series Analysis.Ariel Linden - 2018 - Journal of Evaluation in Clinical Practice 24 (3):502-507.
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  • 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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  • Combining Synthetic Controls and Interrupted Time Series Analysis to Improve Causal Inference in Program Evaluation.Ariel Linden - 2018 - Journal of Evaluation in Clinical Practice 24 (2):447-453.
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  • Using Forecast Modelling to Evaluate Treatment Effects in Single-Group Interrupted Time Series Analysis.Ariel Linden - 2018 - Journal of Evaluation in Clinical Practice 24 (4):695-700.
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  • Using Randomization Tests to Assess Treatment Effects in Multiple-Group Interrupted Time Series Analysis.Ariel Linden - 2019 - Journal of Evaluation in Clinical Practice 25 (1):5-10.
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  • Using Machine Learning to Evaluate Treatment Effects in Multiple-Group Interrupted Time Series Analysis.Ariel Linden & Paul R. Yarnold - 2018 - Journal of Evaluation in Clinical Practice 24 (4):740-744.
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