<p>Competing risk data set involving Hodgkin's disease.</p>

datasets

Fast OpenMP parallel processing for Breiman's random forests for survival, competing risks, regression and classification based on Ishwaran and Kogalur's popular random survival forests (RSF) package.  Handles missing data and now includes multivariate, unsupervised forests and quantile regression.  New fast interface using subsampling.

Udaya Kogalur

randomForestSRC

Random Forests for Survival, Regression, and Classification
(RF-SRC)

hd function

<p>A data frame containing:</p><table><tr><td>
    age      </td>
<td> age</td>
</tr><tr><td>
    sex      </td>
<td> gender</td>
</tr><tr><td>
	  trtgiven </td>
<td> treatment: RT=radition, CMT=Chemotherapy and radiation</td>
</tr><tr><td>
	  medwidsi </td>
<td> mediastinum involvement: N=no, S=small, L=Large</td>
</tr><tr><td>
	  extranod </td>
<td> extranodal disease: Y=extranodal disease, N=nodal disease</td>
</tr><tr><td>
    clinstg	 </td>
<td> clinical stage: 1=stage I, 2=stage II</td>
</tr><tr><td>
    time     </td>
<td> first failure time</td>
</tr></table>

hd: Hodgkin's Disease

Description

Arguments

Format

References

Examples

age	age
sex	gender
trtgiven	treatment: RT=radition, CMT=Chemotherapy and radiation
medwidsi	mediastinum involvement: N=no, S=small, L=Large
extranod	extranodal disease: Y=extranodal disease, N=nodal disease
clinstg	clinical stage: 1=stage I, 2=stage II
time	first failure time