icea

icea_pw

These functions are deprecated, use <code>cea()</code> and <code>cea_pw()</code> instead.

internal

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 

icea function

<dl><dt>x</dt>
<dd>An object of simulation output characterizing the probability distribution
of clinical effectiveness and costs.?ic</dd>
<dt>...</dt>
<dd>Further arguments passed to or from other methods.</dd></dl>

Arguments

Individualized cost-effectiveness analysis — icea

<dl>

<dt>x</dt>
<dd>An object of simulation output characterizing the probability distribution
of clinical effectiveness and costs.?ic</dd>


<dt>...</dt>
<dd>Further arguments passed to or from other methods.</dd>

</dl>

icea: Individualized cost-effectiveness analysis

Description

Usage

Arguments