Urine Data
The urine data frame has 77 rows and 7 columns.
79 urine specimens were analyzed in an effort to determine if certain physical characteristics of the urine might be related to the formation of calcium oxalate crystals.
data(urine)
This data frame contains the following columns:
rindicator of the presence of calcium oxalate crystals;
gravitythe specific gravity of the urine, i.e. the density of urine relative to water;
phthe pH reading of the urine;
osmothe osmolarity of the urine. Osmolarity is proportional to the concentration of molecules in solution (mOsm).
conductThe conductivity of the urine. Conductivity is proportional to the concentration of charged ions in solution (mMho milliMho).
ureathe urea concentration in millimoles per litre;
calcthe calcium concentration in millimoles per litre.
The data were obtained from
Andrews, D. F. and Herzberg, A. M. (1985) Data: A Collection of Problems from Many Fields for the Student and Research Worker, Cambridge: Cambridge University Press.
Davison, A. C. and Hinkley, D. V. (1997). Bootstrap Methods and Their Application (Example 7.8). Cambridge: Cambridge University Press.
data(urine)
summary(urine)
pairs(urine)
##
data(urine)
urine.glm <- glm(r ~ gravity + ph + osmo + conduct + urea + log(calc),
family = binomial, data = urine)
labels(coef(urine.glm))
urine.cond <- cond(urine.glm, log(calc))
##
## (large estimate of regression coefficient)
urine.glm <- glm(r ~ gravity + ph + osmo + conduct + urea + calc,
family = binomial, data = urine)
coef(urine.glm)
urine.glm <- glm(r ~ I(gravity * 100) + ph + osmo + conduct + urea + calc,
family = binomial, data = urine)
coef(urine.glm)
urine.cond <- cond(urine.glm, I(gravity * 100))Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.