stateprobs

An object of class <code>stateprobs</code> returned by <code>sim_stateprobs()</code> or from
<code>$sim_stateprobs()</code> methods in model classes.

A modular and computationally efficient R package for
parameterizing, simulating, and analyzing health economic simulation
models. The package supports cohort discrete time state transition models
(Briggs et al. 1998) <doi:10.2165/00019053-199813040-00003>,
N-state partitioned survival models (Glasziou et al. 1990)
<doi:10.1002/sim.4780091106>, and individual-level continuous
time state transition models (Siebert et al. 2012) <doi:10.1016/j.jval.2012.06.014>,
encompassing both Markov (time-homogeneous and time-inhomogeneous) and
semi-Markov processes. Decision uncertainty from a cost-effectiveness analysis is
quantified with standard graphical and tabular summaries of a probabilistic
sensitivity analysis (Claxton et al. 2005, Barton et al. 2008) <doi:10.1002/hec.985>,
<doi:10.1111/j.1524-4733.2008.00358.x>. Use of C++ and data.table
make individual-patient simulation, probabilistic sensitivity analysis,
and incorporation of patient heterogeneity fast.

Devin Incerti

hesim

Health Economic Simulation Modeling and Decision Analysis

Jeroen P. Jansen

Mark Clements

R Core Team 

stateprobs function

A <code>stateprobs</code> object inherits from <code>data.table</code> and contains
the following columns:
<dl>
<dt>sample</dt>
<dd>A random sample from the PSA.</dd><dt>strategy_id</dt>
<dd>The treatment strategy ID.</dd><dt>patient_id</dt>
<dd>The patient ID.</dd><dt>grp_id</dt>
<dd>The subgroup ID.</dd><dt>state_id</dt>
<dd>The health state ID.</dd><dt>t</dt>
<dd>The time at which a state probability is computed.</dd><dt>prob</dt>
<dd>The probability of being in a given health state.</dd>
</dl>When simulating individual-level models, the <code>patient_id</code> column is
not included as state probabilities are computed by averaging across patients.
In cohort models, the object also contains <code>size</code> and <code>absorbing</code> attributes.
The <code>size</code> attribute is a numeric vector with the elements <code>n_samples</code>,
<code>n_strategies</code>, <code>n_patients</code>, <code>n_states</code>, and
<code>n_times</code> denoting the number of samples, treatment strategies, patients,
health states, and times. The <code>absorbing</code> attribute is a numeric vector
containing the absorbing health states (see the <code>absorbing</code> field of the
<code>CohortDtstmTrans</code> class for more details).

Components

State probability object — stateprobs

A <code>stateprobs</code> object inherits from <code>data.table</code> and contains
the following columns:
<dl>
<dt>sample</dt>
<dd>A random sample from the PSA.</dd>

<dt>strategy_id</dt>
<dd>The treatment strategy ID.</dd>

<dt>patient_id</dt>
<dd>The patient ID.</dd>

<dt>grp_id</dt>
<dd>The subgroup ID.</dd>

<dt>state_id</dt>
<dd>The health state ID.</dd>

<dt>t</dt>
<dd>The time at which a state probability is computed.</dd>

<dt>prob</dt>
<dd>The probability of being in a given health state.</dd>


</dl>

When simulating individual-level models, the <code>patient_id</code> column is
not included as state probabilities are computed by averaging across patients.
In cohort models, the object also contains <code>size</code> and <code>absorbing</code> attributes.
The <code>size</code> attribute is a numeric vector with the elements <code>n_samples</code>,
<code>n_strategies</code>, <code>n_patients</code>, <code>n_states</code>, and
<code>n_times</code> denoting the number of samples, treatment strategies, patients,
health states, and times. The <code>absorbing</code> attribute is a numeric vector
containing the absorbing health states (see the <code>absorbing</code> field of the
<code>CohortDtstmTrans</code> class for more details).

stateprobs: State probability object

Description

Arguments

Components