Use a logistic regression to model the odds of death

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Reference no: EM131431690

An example of Simpson's paradox. Here is an example of Simpson's paradox, the reversal of the direction of a comparison or an association when data from several groups are combined to form a single group. The data concern two hospitals, A and B, and whether or not patients undergoing surgery died or survived. Here are the data for all patients:

 

Hospital A

Hospital B

Died

63

16

Survived

2037

784

Total

2100

800

And here are the more detailed data where the patients are categorized as being in good condition or poor condition before having the surgery

Good condition

 

Hospital A

Hospital B

Died

6

8

Survived

594

592

Total

600

600



Poor condition

 

Hospital A

Hospital B

Died

57

8

Survived

1443

192

Total

1500

200

(a) Use a logistic regression to model the odds of death with hospital as the explanatory variable. Summarize the results of your analysis and give a 95% confidence interval for the odds ratio of Hospital A relative to Hospital B.

(b) Rerun your analysis in part (a) using hospital and the condition of the patient as explanatory variables. Summarize the results of your analysis and give a 95% confidence interval for the odds ratio of Hospital A relative to Hospital B.

(c) Explain Simpson's paradox in terms of your results in parts (a) and (b).

Reference no: EM131431690

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