{"args":{},"checks":[{"abs_tol":null,"bind":"any","column":null,"failure_class":null,"field":"value","interval":false,"key":null,"kind":"answer_backed","min_lre":null,"note":"every number of the answer is stated by a tool call","open_interval":false,"rel_tol":null,"required":true,"source_id":null,"table":null,"tool":null,"value":null,"weight":1.0,"where":null},{"abs_tol":null,"bind":"answer_call","column":null,"failure_class":null,"field":"value","interval":true,"key":null,"kind":"answer_figure_close","min_lre":null,"note":"QRData eval.py: strictly inside gold \u00b1 3% (a '%' gold divided by 100), on the answer figure after meta.answer_format","open_interval":true,"rel_tol":null,"required":true,"source_id":"qrdata.gold.357","table":null,"tool":null,"value":[-7.8177,-7.362299999999999],"weight":1.0,"where":null}],"datasets":{"hospital_treatment":{"columns":null,"description":"The dataset hospital_treatment.csv includes data from a randomized trial conducted by two hospitals. Both of them are conducting randomised trials on a new drug to treat a certain illness. The outcome of interest is days hospitalised. If the treatment is effective, it will lower the amount of days the patient stays in the hospital. For one of the hospitals, the policy regarding the random treatment is to give it to 90% of its patients while 10% get a placebo. The other hospital has a different policy: it gives the drug to a random 10% of its patients and 90% get a placebo. You are also told that the hospital that gives 90% of the true drug and 10% of placebo usually gets more severe cases of the illness to treat. The CSV file contains columns for `hospital` indicating the hospital a patient belongs to, `treatment` signifying if the patient received the new drug or placebo, `severity` reflecting the severity of the illness, and `days` representing the number of days the patient was hospitalized.","file_sha256":"3c3a97cca6fdd96f6856f7856b5f8bc786a31d1a9be78c9f610ef3070783e970","format":"csv","frame_sha256":null,"generator":null,"kind":"file","licence":"CC BY-NC 4.0","member":"data/hospital_treatment.csv","object":null,"params":{},"path":null,"read_kw":{},"records":null,"role":"agent","sha256":"3c3a97cca6fdd96f6856f7856b5f8bc786a31d1a9be78c9f610ef3070783e970","transforms":[],"url":"https://raw.githubusercontent.com/xxxiaol/QRData/de450af45ff7101b328bb064c6b475f73414a7ed/benchmark/data.zip"}},"difficulty":"M","id":"qrdata_socsci.357","level":"T2","meta":{"agent_reach":{"blocked_by":[],"dtypes":{"hospital_treatment":{"days":"int64","severity":"float64","treatment":"int64"}},"named":{"outcome":["days"],"treatment":["treatment"]},"reachable":true,"rule":"magi_bench.reach/1"},"answer_format":{"figure_transform":"identity","round_to":2,"unit_scale":1.0},"answer_format_from":{"figure_transform":null,"round_to":"nearest hundredth","unit_scale":"1.0: an estimator's figure is on the gold's own scale"},"cluster":"hospital_treatment.csv","expected_tool":"infer.ols","family":"numerical","headline_keys":{"infer.ols":["coef.treatment"]},"naive":{"dataset":"hospital_treatment","treatment":"treatment","y":"days"},"native":{"answer":"-7.59","keywords":["Causality","Randomized experiment","Regression analysis","Average treatment effect","Confounder selection"],"multiple_choices":null,"question_type":"numerical","reference":"Causal Inference for the Brave and True 7"},"native_id":357,"reference":{"cite":1,"note":"Caminho de refer\u00eancia inferido \u00e0 m\u00e3o.","steps":[{"args":{"controls":["severity"],"dataset":"hospital_treatment","x":["treatment"],"y":"days"},"tool":"infer.ols","why":"OLS of days on treatment controlling for severity, the confounder of the two hospitals' assignment rates."}]},"reference_path":{"calls":[{"args":{"controls":["severity"],"dataset":"hospital_treatment","x":["treatment"],"y":"days"},"tool":"infer.ols"}],"needs":[],"provenance":"hand_inferred","quotes":{},"reference_datasets":[],"source_id":null},"reference_why":"OLS of days on treatment controlling for severity, the confounder of the two hospitals' assignment rates."},"question":"What is the average treatment effect (ATE) of the new drug on the amount of days the patient stays in the hospital? Please choose the variables to adjust for, conduct linear regression, and round your answer to the nearest hundredth. If the new drug reduces the amount of days the patient stays in the hospital, the answer should be negative.","requires":[],"runner":null,"sources":["qrdata.gold.357","qrdata.eval_py"],"split":"public","suite":"qrdata_socsci","tags":["econ-bench","external","qrdata","brave_and_true","numerical","reference_path","agent_reachable","naive"],"target":"agent","tool":null,"truth":"QRData gold: benchmark/QRData.json item 357 at de450af45ff7101b328bb064c6b475f73414a7ed"}