Replication Data for: Qualitative Imputation of Missing Potential Outcomes
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully.  <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'We propose a framework for meta-analysis of qualitative causal inferences. We integrate qualitative counterfactual inquiry with an approach from the quantitative causal inference literature called extreme value bounds. Qualitative counterfactual analysis uses the observed outcome and auxiliary information to infer what would have happened had the treatment been set to a different level. Imputing missing potential outcomes is hard and when it fails, we can fill them in under best- and worst-case scenarios. We apply our approach to 63 cases that could have experienced transitional truth commissions upon democratization, 8 of which did. Prior to any analysis, the extreme value bounds around the average treatment effect on authoritarian resumption are 100 percentage points wide; imputation shrinks the width of these bounds to 51 points. We ' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Potential outcomes","Qualitative inference"]} <|eot_id|>
 Here is the Description of a dataset. Description:'We propose a framework for meta-analysis of qualitative causal inferences. We integrate qualitative counterfactual inquiry with an approach from the quantitative causal inference literature called extreme value bounds. Qualitative counterfactual analysis uses the observed outcome and auxiliary information to infer what would have happened had the treatment been set to a different level. Imputing missing potential outcomes is hard and when it fails, we can fill them in under best- and worst-case scenarios. We apply our approach to 63 cases that could have experienced transitional truth commissions upon democratization, 8 of which did. Prior to any analysis, the extreme value bounds around the average treatment effect on authoritarian resumption are 100 percentage points wide; imputation shrinks the width of these bounds to 51 points. We ' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
We propose a framework for meta-analysis of qualitative causal inferences. We integrate qualitative counterfactual inquiry with an approach from the quantitative causal inference literature called extreme value bounds. Qualitative counterfactual analysis uses the observed outcome and auxiliary information to infer what would have happened had the treatment been set to a different level. Imputing missing potential outcomes is hard and when it fails, we can fill them in under best- and worst-case scenarios. We apply our approach to 63 cases that could have experienced transitional truth commissions upon democratization, 8 of which did. Prior to any analysis, the extreme value bounds around the average treatment effect on authoritarian resumption are 100 percentage points wide; imputation shrinks the width of these bounds to 51 points. We 
Potential outcomes; Qualitative inference