qcond_lnorm

Conditional quantile function for lognormal distribution

Toolkit to support and perform discrete event simulations without
resource constraints in the context of health technology assessments (HTA).
The package focuses on cost-effectiveness modelling and aims to be submission-ready
to relevant HTA bodies in alignment with 'NICE TSD 15'
<https://www.sheffield.ac.uk/nice-dsu/tsds/patient-level-simulation>.
More details an examples can be found in the package website <https://jsanchezalv.github.io/WARDEN/>.

Javier Sanchez Alvarez

WARDEN

Workflows for Health Technology Assessments in R using Discrete
EveNts

Gabriel Lemyre

Valerie Aponte Ribero

qcond_lnorm function

<dl><dt>rnd</dt>
<dd>Vector of quantiles</dd>
<dt>meanlog</dt>
<dd>The meanlog parameter</dd>
<dt>sdlog</dt>
<dd>The sdlog parameter</dd>
<dt>lower_bound</dt>
<dd>The lower bound to be used (current time)</dd>
<dt>s_obs</dt>
<dd>is the survival observed up to lower_bound time,
normally defined from time 0 as 1 - plnorm(q = lower_bound, meanlog, sdlog) but may be different if parametrization has changed previously</dd></dl>

Arguments

Conditional quantile function for lognormal distribution — qcond_lnorm

<dl>

<dt>rnd</dt>
<dd>Vector of quantiles</dd>


<dt>meanlog</dt>
<dd>The meanlog parameter</dd>


<dt>sdlog</dt>
<dd>The sdlog parameter</dd>


<dt>lower_bound</dt>
<dd>The lower bound to be used (current time)</dd>


<dt>s_obs</dt>
<dd>is the survival observed up to lower_bound time,
normally defined from time 0 as 1 - plnorm(q = lower_bound, meanlog, sdlog) but may be different if parametrization has changed previously</dd>

</dl>

qcond_lnorm: Conditional quantile function for lognormal distribution

Description

Usage

Value

Arguments

Examples