Urinary Incontinence Study
Description
Data from urinary incontinence study analyzed by Preisser and Qaqish (1999).
Usage
data(ui)
Format
A data frame with 137 observations on the following 12 variables.
pract_id
- cluster id: used for identifying the practice
doct_id
- doctor's id: used for identifying the doctors in the practice
pat_id
- patient's id: used for identifying the patients in the practice
bothered
- response: whether patient's condition is bothersome
female
- indicator for female
ageyrs
- patient's age
age
- standardized age: (age - 76)/10
weekacc
- patient report of number of leaking accidents they experienced in an average week
dayacc
- patient report of number of leaking accidents they experienced in an average day
severe
- severity of loss of urine: 1 if there is only moisture, 2 if the patient wet the underwear,
3 if the urine trickled down the thigh, and 4 if the patient wet the floor
toilet
- number of times patient frequents the toilet to urinate (in a day)
mdage
- age of the doctors in the practice
References
Hammil, B. G., Preisser, J. S., A SAS/IML software program for GEE and regression diagnostics,
Computational Statistics and Data Analysis, 51: 1197 - 1212, 2006.
Preisser, J. S., Qaqish, B. F., Robust regression for clustered data with application to binary responses,
Biometrics, 55: 574-579, 1999.
[Package
orth version 1.5
Index]