popmort


  Background mortality rates for the colon dataset.


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

popmort function

A data frame with 10600 observations on the following 5 variables.
  <dl>
    <dt><code>sex</code></dt><dd>Sex (1=male, 2=female)</dd> <dt><code>prob</code></dt><dd>One year probability of survival</dd> <dt><code>rate</code></dt><dd>All cause mortality rate</dd> <dt><code>age</code></dt><dd>Age by single year of age through to age 105 years</dd> <dt><code>year</code></dt><dd>Calendar period</dd> </dl> 

popmort: Background mortality rates for the colon dataset.

Description

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Examples