residuals-methods

residuals,stpm2-method

residuals,pstpm2-method

an <code>stpm2</code> or <code>pstpm2</code> object

object

specify the type of residuals:<ul>
<li>"li"log-likelihood components (not strictly residuals)</li>
<li>"gradli"gradient of the log-likelihood components (not
 strictly residuals)</li>
</ul>

type

Given an <code>stpm2</code> or <code>pstpm2</code> fit, return residuals

methods

R implementation of generalized survival models (GSMs) and smooth accelerated failure time (AFT) models. For the GSMs, 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 with natural splines, 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. For the smooth AFTs, S(t|x) = S_0(t*eta(t,x)), where the baseline survival function S_0(t)=exp(-exp(eta_0(t))) is modelled for natural splines for eta_0, and the time-dependent cumulative acceleration factor eta(t,x)=\int_0^t exp(eta_1(u,x)) du for log acceleration factor eta_1(u,x).

Mark Clements

rstpm2

Generalized Survival Models

Xing-Rong Liu

Paul Lambert

Lasse Hjort Jakobsen

Alessandro Gasparini

Gordon Smyth

Patrick Alken

Simon Wood

Rhys Ulerich

residuals-methods function

<dl class="dl-horizontal">
 <dt>object= "stpm2"</dt><dd>an <code>stpm2</code> fit</dd>
</dl>

Methods

Residual values for an stpm2 or pstpm2 fit — residuals-methods

<dl class='dl-horizontal'>
 <dt>object= "stpm2"</dt><dd>an <code>stpm2</code> fit</dd>
</dl>

residuals-methods: Residual values for an stpm2 or pstpm2 fit

Description

Usage

Arguments

Value

Methods

Details

See Also