The data set readmit.sav gives part of the data from a study of 1034 New Zealand children who had been discharged from hospital following an admission for asthma (Mitchell et al., 1994). The authors wanted to find what factors predicted discharge. In particular, some of the children had been discharged with a written crisis plan, to help their parents deal with any subsequent exacerbations of asthma. Would this help to reduce the risk of admission?
Load the data set readmit.sav and start SPSS.
1. How many children are there and how many were readmitted?
2. Draw a survival curve for time to readmission to hospital.
3. Plot the survival for children discharged with and without a crisis plan and test the null hypothesis that readmission is unrelated to the presence of a crisis plan.
How do children given a crisis plan differ from the other children?
5. Which two of these predictor variables would you expect to be related to one another, whatever the disease in question?
6. What is the best estimate of the effect of the crisis plan? Give a confidence interval for the estimate. How do the other variables predict readmission?
8. Can we conclude giving a family a crisis plan increases the child's chance of being readmitted?
To Biostatistics in Research Practice index.
To Martin Bland's M.Sc. index.
This page maintained by Martin Bland.
Last updated: 6 February, 2008.