colon

datasets

R implementation of generalized survival models, where g(S(t|x))=eta(t,x) for a link function g, survival S at time t with covariates x and a linear predictor eta(t,x). The main assumption is that the time effect(s) are smooth. For fully parametric models, this re-implements Stata's 'stpm2' function, which are flexible parametric survival models developed by Royston and colleagues. We have extended the parametric models to include any smooth parametric smoothers for time. We have also extended the model to include any smooth penalized smoothers from the 'mgcv' package, using penalized likelihood. These models include left truncation, right censoring, interval censoring, gamma frailties and normal random effects.

Mark Clements

rstpm2

Generalized Survival Models

colon function

A data frame with 15564 observations on the following 13 variables.
  <dl>
<dt><code>sex</code></dt><dd>Sex (1=male, 2=female))</dd> <dt><code>age</code></dt><dd>Age at diagnosis</dd> <dt><code>stage</code></dt><dd>Clinical stage at diagnosis  (1=Unknown,
      2=Localised, 3=Regional, 4=Distant)</dd> <dt><code>mmdx</code></dt><dd>Month of diagnosis</dd> <dt><code>yydx</code></dt><dd>Year of diagnosis</dd> <dt><code>surv_mm</code></dt><dd>Survival time in months</dd> <dt><code>surv_yy</code></dt><dd>Survival time in years</dd> <dt><code>status</code></dt><dd>Vital status at last contact (1=Alive,
  2=Dead: cancer, 3=Dead; other, 4=Lost to follow-up)</dd> <dt><code>subsite</code></dt><dd>Anatomical subsite of tumour (1=Coecum and
  ascending, 2=Transverse, 3=Descending and sigmoid, 4=Other and NOS)</dd> <dt><code>year8594</code></dt><dd>Year of diagnosis (1=Diagnosed 75-84, 2=Diagnosed
  85-94)</dd> <dt><code>agegrp</code></dt><dd>Age in 4 categories (1=0-44, 2=45-59, 3=60-74, 4=75+)</dd> <dt><code>dx</code></dt><dd>Date of diagnosis</dd> <dt><code>exit</code></dt><dd>Date of exit</dd> </dl> 

colon: Colon cancer.

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