data

Simulated data in which the individuals can move from the initial 
 state (State 1) to an intermediate state (State 2). From there, they may 
 either proceed to the absorbing state (State 4), passing through another 
 intermediate state (State 3), or move directly from the initial state to the 
 absorbing state.

datasets

Multi-state models are essential tools in longitudinal data analysis.
One primary goal of these models is the estimation of transition
probabilities, a critical metric for predicting clinical prognosis
across various stages of diseases or medical conditions. Traditionally,
inference in multi-state models relies on the Aalen-Johansen (AJ)
estimator which is consistent under the Markov assumption. However,
in many practical applications, the Markovian nature of the process
is often not guaranteed, limiting the applicability of the AJ
estimator in more complex scenarios. This package extends the landmark Aalen-Johansen
estimator (Putter, H, Spitoni, C (2018) <doi:10.1177/0962280216674497>)
incorporating presmoothing techniques described by Soutinho,
Meira-Machado and Oliveira (2020) <doi:10.1080/03610918.2020.1762895>,
offering a robust alternative for estimating transition probabilities
in non-Markovian multi-state models with multiple states and potential
reversible transitions.

Gustavo Soutinho

presmoothedTP

Presmoothed Landmark Aalen-Johansen Estimator of Transition
Probabilities for Complex Multi-State Models

Luis Meira-Machado

data function

A data frame with 500 observations on the following 6 variables.<dl>
 <dt><code>y1</code></dt>
<dd>First gap time.</dd> <dt><code>state1</code></dt>
<dd>Indicator of the first gap time; 0 if the first time is 
 censored and 1 otherwise.</dd> <dt><code>y2</code></dt>
<dd>Second gap time.</dd> <dt><code>state2</code></dt>
<dd>Censoring indicator of the second gap time; 0 if the total 
 time is censored and 1 otherwise.</dd> <dt><code>y3</code></dt>
<dd>Third gap time.</dd> <dt><code>state3</code></dt>
<dd>Censoring indicator of the third gap time; 0 if the total 
 time is censored and 1 otherwise.</dd> 
</dl>

Format

data — data

A data frame with 500 observations on the following 6 variables.<dl>
 <dt><code>y1</code></dt>
<dd>First gap time.</dd>

 <dt><code>state1</code></dt>
<dd>Indicator of the first gap time; 0 if the first time is 
 censored and 1 otherwise.</dd>

 <dt><code>y2</code></dt>
<dd>Second gap time.</dd>

 <dt><code>state2</code></dt>
<dd>Censoring indicator of the second gap time; 0 if the total 
 time is censored and 1 otherwise.</dd>

 <dt><code>y3</code></dt>
<dd>Third gap time.</dd>

 <dt><code>state3</code></dt>
<dd>Censoring indicator of the third gap time; 0 if the total 
 time is censored and 1 otherwise.</dd>

 
</dl>

data: data

Description

Usage

Arguments

Format

Examples