A data set consisting of variables of mixed type measured on a group of prostate cancer patients. Patients have either stage 3 or stage 4 prostate cancer.
A data frame with 475 observations on the following 15 variables.
a numeric vector indicating the age of the patient.
a numeric vector indicating the weight of the patient.
an ordinal variable indicating how active the patient is: 0 - normal activity, 1 - in bed less than 50% of daytime, 2 - in bed more than 50% of daytime, 3 - confined to bed.
a binary variable indicating if the patient has a history of cardiovascular disease: 0 - no, 1 - yes.
a numeric vector indicating the systolic blood pressure of the patient in units of ten.
a numeric vector indicating the diastolic blood pressure of the patient in units of ten.
a nominal variable indicating the electorcardiogram code: 0 - normal, 1 - benign, 2 - rythmic disturbances and electrolyte changes, 3 - heart blocks or conduction defects, 4 - heart strain, 5 - old myocardial infarct, 6 - recent myocardial infarct.
a numeric vector indicating the serum haemoglobin levels of the patient measured in g/100ml.
a numeric vector indicating the estimated size of the patient's primary tumour in centimeters squared.
a numeric vector indicating the combined index of tumour stage and histolic grade of the patient.
a numeric vector indicating the serum prostatic acid phosphatase levels of the patient in King-Armstong units.
a binary vector indicating the presence of bone metastasis: 0 - no, 1 - yes.
the stage of the patient's prostate cancer.
a patient ID number.
the post trial survival status of the patient: 0 - alive, 1 - dead from prostatic cancer, 2 - dead from heart or vascular disease, 3 - dead from cerebrovascular accident, 3 - dead form pulmonary ebolus, 5 - dead from other cancer, 6 - dead from respiratory disease, 7 - dead from other specific non-cancer cause, 8 - dead from other unspecified non-cancer cause, 9 - dead from unknown cause.
Byar, D.P. and Green, S.B. (1980). The choice of treatment for cancer patients based on covariate information: applications to prostate cancer. Bulletin du Cancer 67: 477-490.
Hunt, L., Jorgensen, M. (1999). Mixture model clustering using the multimix program. Australia and New Zealand Journal of Statistics 41: 153-171.
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