prostate: Prostate Cancer Data

In RMixtComp: Mixture Models with Heterogeneous and (Partially) Missing Data

Prostate Cancer Data

Description

This data set was obtained from a randomized clinical trial comparing four treatments for n = 506 patients with prostatic cancer grouped on clinical criteria into two Stages 3 and 4 of the disease.

Usage

data(prostate)

Format

A list containing of 2 elements data and model. data contains 506 individuals described by 12 variables:

• Age: Age (Continuous)

• HG: Index of tumour stage and histolic grade (Continuous)

• Wt: Weight (Continuous)

• AP: Serum prostatic acid phosphatase C (Continuous)

• SBP: Systolic blood pressure (Continuous)

• PF: Performance rating (Categorical)

• DBP: Diastolic blood pressure (Continuous)

• HX: Cardiovascular disease history (Categorical)

• SG: Serum haemoglobin (Continuous)

• BM: Bone metastasis (Categorical)

• SZ: Size of primary tumour (Continuous)

• EKG: Electrocardiogram code (Categorical)

Source

Yakovlev, Goot and Osipova (1994), The choice of cancer treatment based on covariate information. Statist. Med., 13: 1575-1581. doi:10.1002/sim.4780131508

See Also

Other data: CanadianWeather, simData, titanic

Examples

data(prostate)

algo <- createAlgo(nInitPerClass = 50)

# run clustering
resLearn <- mixtCompLearn(prostate$data, prostate$model, algo,
    nClass = 2:5, criterion = "ICL",
    nRun = 3, nCore = 1
)

summary(resLearn)

plot(resLearn)

RMixtComp documentation built on July 9, 2023, 6:06 p.m.