Replication Data for: An Equivalence Approach to Balance and Placebo Tests
<|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:'Recent emphasis on credible causal designs has led to the expectation that scholars justify their research designs by testing the plausibility of their causal identification assumptions, often through balance and placebo tests. Yet current practice is to use statistical tests with  an inappropriate null hypothesis of no difference, which can result in  the equating of non-significant differences with significant homogeneity. Instead, we argue that researchers should begin with the initial hypothesis that the data is inconsistent with a valid research design, and provide sufficient statistical evidence in favor of a valid design. When tests are correctly specified so that difference is the null and equivalence is the alternative, the problems afflicting traditional tests are alleviated. We argue that equivalence tests are better able to ' . 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" : ["Balance tests","Equivalence tests","Falsification tests","Placebo tests"]} <|eot_id|>
 Here is the Description of a dataset. Description:'Recent emphasis on credible causal designs has led to the expectation that scholars justify their research designs by testing the plausibility of their causal identification assumptions, often through balance and placebo tests. Yet current practice is to use statistical tests with  an inappropriate null hypothesis of no difference, which can result in  the equating of non-significant differences with significant homogeneity. Instead, we argue that researchers should begin with the initial hypothesis that the data is inconsistent with a valid research design, and provide sufficient statistical evidence in favor of a valid design. When tests are correctly specified so that difference is the null and equivalence is the alternative, the problems afflicting traditional tests are alleviated. We argue that equivalence tests are better able to ' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
Recent emphasis on credible causal designs has led to the expectation that scholars justify their research designs by testing the plausibility of their causal identification assumptions, often through balance and placebo tests. Yet current practice is to use statistical tests with  an inappropriate null hypothesis of no difference, which can result in  the equating of non-significant differences with significant homogeneity. Instead, we argue that researchers should begin with the initial hypothesis that the data is inconsistent with a valid research design, and provide sufficient statistical evidence in favor of a valid design. When tests are correctly specified so that difference is the null and equivalence is the alternative, the problems afflicting traditional tests are alleviated. We argue that equivalence tests are better able to 
Balance tests; Equivalence tests; Falsification tests; Placebo tests