The data, 1383 observations, are from a study at the Hospital del Mar, Barcelona during the years 1988 and 1990, Gange et al. (1996).
data(aep)A data frame with 1383 observations on the following 8 variables.
the total number of days patients spent in hospital: a discrete vector
the number of inappropriate days spent in hospital: a discrete vector
the log(los/10): a numeric vector
the gender of patient: a factor with levels 1=male, 2=female
the type of ward in the hospital: a factor with levels 1=medical 2=surgical, 3=others
the specific year 1988 or 1990: a factor with levels 88 and 90
the age of the patient subtracted from 55: a numeric vector
the response variable a matrix with 2 columns, the first is noinap the second is equal to (los-noinap)
Gange et al. (1996) used a logistic regression model for the number of inappropriate days (noinap) out of the total number of days spent in hospital (los), with binomial and beta binomial errors and found that the later provided a better fit to the data. They modelled both the mean and the dispersion of the beta binomial distribution (BB) as functions of explanatory variables
Gange, S. J. Munoz, A. Saez, M. and Alonso, J. (1996) Use of the beta-binomial distribution to model the effect of policy changes on appropriateness of hospital stays. Appl. Statist, 45, 371--382
data(aep)
attach(aep)
pro<-noinap/los
plot(ward,pro)
rm(pro)
detach(aep)
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