simpson paradox 标注 case1

simpson paradox...

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simpson's paradox As with quantitative variables, the effects of lurking variables can change or even reverse relationships between two categorical variables. Here is a hypothetical example that demonstrates the surprises that can await the unsuspecting consumer of data. Example In an attempt to help consumers make informed decisions about health care, the government releses data about patient outcomes in a large number of hospitals. You are interested in comparing Hosoital A and Hospital B, which serve your community Here are the data on the survival of patients after surgery in these two hospitals. All patients undergoing surgery in a recent time period are included; “survived” means that the patient lived at lest 6 weeks following surgerty. Hospital A Hospital B Died 63 16 Survived 2037 784 Total 2100 800 The evidence seems clear: Hospital A loses 3% (63/2100) of its surgery patients, whereas Hospital B loses only 2% (16/800). It seems that you should choose Hospital B when you next need surgery: Not all surgery cases are equally serious, however. Later in the government report you find data on the outcome of surgery broken down by the condition of the patient before the operation. Patients
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This note was uploaded on 06/02/2011 for the course ECONOMICS 101 taught by Professor Youalreadyknow during the Spring '11 term at Punjab Engineering College.

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simpson paradox...

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