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          "target": "All observed treated observations, using configured observation weights; cell mass equals sum of row weights",
          "status": "estimated"
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        {
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          "status": "failed",
          "reason": "RuntimeError: multisynth-cohort failed; see multisynth-cohort.log"
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        {
          "method": "Multisynth (individual)",
          "status": "failed",
          "reason": "RuntimeError: multisynth-individual failed; see multisynth-individual.log"
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    "combined_table": [
      {
        "Outcome / treatment": "y__d",
        "Estimator": "Static TWFE",
        "Estimate (SDs)": -0.27750585099621405,
        "SE": 0.06060034071133945,
        "Aggregation": "Coefficient",
        "Event study": "No",
        "Status": "estimated",
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      {
        "Outcome / treatment": "y__d",
        "Estimator": "Dynamic TWFE",
        "Estimate (SDs)": -1.5226491841356031,
        "SE": 0.0494592116093022,
        "Aggregation": "observations",
        "Event study": "Yes",
        "Status": "estimated",
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      {
        "Outcome / treatment": "y__d",
        "Estimator": "BJS / did2s",
        "Estimate (SDs)": -2.082259030221016,
        "SE": 0.04684774998927659,
        "Aggregation": "observations",
        "Event study": "Yes",
        "Status": "estimated",
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      {
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        "Estimator": "Sun\u2013Abraham",
        "Estimate (SDs)": -1.285328618279391,
        "SE": 0.016872209466546377,
        "Aggregation": "observations",
        "Event study": "Yes",
        "Status": "estimated",
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      {
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        "Estimator": "CS-DID",
        "Estimate (SDs)": null,
        "SE": null,
        "Aggregation": "Equal post-event times",
        "Event study": "No",
        "Status": "failed",
        "Note": "ValueError: Missing values at att_gt found. If you want to remove these, set `na_rm = True`."
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      {
        "Outcome / treatment": "y__d",
        "Estimator": "SDID",
        "Estimate (SDs)": -3.1880929769495023,
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        "Aggregation": "Treated cells",
        "Event study": "Yes",
        "Status": "estimated",
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      {
        "Outcome / treatment": "y__d",
        "Estimator": "Matrix completion",
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        "SE": null,
        "Aggregation": "Treated cells",
        "Event study": "Yes",
        "Status": "estimated",
        "Note": ""
      },
      {
        "Outcome / treatment": "y__d",
        "Estimator": "Horizontal ridge",
        "Estimate (SDs)": -0.12062387714144174,
        "SE": null,
        "Aggregation": "Treated cells",
        "Event study": "Yes",
        "Status": "estimated",
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      {
        "Outcome / treatment": "y__d",
        "Estimator": "Multisynth (cohort-averaged)",
        "Estimate (SDs)": null,
        "SE": null,
        "Aggregation": "Treated cells",
        "Event study": "No",
        "Status": "failed",
        "Note": "RuntimeError: multisynth-cohort failed; see multisynth-cohort.log"
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      {
        "Outcome / treatment": "y__d",
        "Estimator": "Multisynth (individual)",
        "Estimate (SDs)": null,
        "SE": null,
        "Aggregation": "Treated cells",
        "Event study": "No",
        "Status": "failed",
        "Note": "RuntimeError: multisynth-individual failed; see multisynth-individual.log"
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      "csdid_general.py": "07619c3b3dfee796ae9e4842afdbc6e367a74cece254ede73f7c403dfc924f6d",
      "runner.py": "3d6f87d28c1a24f0efe21b6d9b06d77866b0d16abcfdaaaef47465cc9cc1078e",
      "matrix_inputs.py": "3f675276f9022147996dd5b62762721be2dd436d5db171491a286b05628176ae",
      "csdid_model.py": "b9fd5536d4886e99a707d2b162db5b11da3ff463930eca5b7590d27500096a3f",
      "multisynth_model.R": "3ae0740c5b75b14f563dacc9961688e8286655866a6b435045a3ef6f453c1604",
      "csdid_streaming.py": "378198e98c44bd46862601bdcb514b19d9ea4038cddc38dad7fdba9b0aa0216b",
      "multisynth_sparse.R": "f9ab3d8d7f7b52a79ccd694c7173f626276a0830f23bb79e527c88c0f0292540",
      "matrix_models.py": "dc7188bf9bf709f0803169dfc3b1198e8b9d2b79d5904ebc5f010a48edde2ee2",
      "csdid_aggregations.py": "cbed0fb13450d9398f9a59d53dbfdf8e275a74daa01158c38c0f3396a3e8c6ee",
      "bootstrap_matrix.py": "a55b171313d43a703063c87e668021b75eb3153fa30795b9ae3d9e2721d9b9d0",
      "eligibility.py": "f0eb686ff3f13e89c8f3d85f49890601c4a7f9a611a2938753be599b8ceac9a6"
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}