Replication Data for: “From ‘Is it unconfounded?’ to ‘How much confounding would it take?’: Applying the sensitivity-based approach to assess causes of support for peace in Colombia”
<|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:'Attention to the credibility of causal claims has increased tremendously in recent years.When relying on observational data, debate often centers on whether investigators have ruled out any bias due to confounding. However, the relevant scientific question is generally not whether bias is precisely zero, but whether it is problematic enough to alter one's research conclusion. We argue that sensitivity analyses would improve research practice by showing how results would change under plausible degrees of confounding, or equivalently, by revealing what one must argue about the strength of confounding to sustain a research conclusion. This would improve scrutiny of studies in which non-zero bias is expected, and of those where authors argue for zero bias but results may be fragile to confounding too weak to be ruled out. We illustrate thi' . 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" : ["FARC referendum","sensemakr","Sensitivity analysis"]} <|eot_id|>
 Here is the Description of a dataset. Description:'Attention to the credibility of causal claims has increased tremendously in recent years.When relying on observational data, debate often centers on whether investigators have ruled out any bias due to confounding. However, the relevant scientific question is generally not whether bias is precisely zero, but whether it is problematic enough to alter one's research conclusion. We argue that sensitivity analyses would improve research practice by showing how results would change under plausible degrees of confounding, or equivalently, by revealing what one must argue about the strength of confounding to sustain a research conclusion. This would improve scrutiny of studies in which non-zero bias is expected, and of those where authors argue for zero bias but results may be fragile to confounding too weak to be ruled out. We illustrate thi' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
Attention to the credibility of causal claims has increased tremendously in recent years.When relying on observational data, debate often centers on whether investigators have ruled out any bias due to confounding. However, the relevant scientific question is generally not whether bias is precisely zero, but whether it is problematic enough to alter one's research conclusion. We argue that sensitivity analyses would improve research practice by showing how results would change under plausible degrees of confounding, or equivalently, by revealing what one must argue about the strength of confounding to sustain a research conclusion. This would improve scrutiny of studies in which non-zero bias is expected, and of those where authors argue for zero bias but results may be fragile to confounding too weak to be ruled out. We illustrate thi
FARC referendum; sensemakr; Sensitivity analysis