simulated_data_norm

datasets

EQ-5D value set estimation can be done using the hybrid model likelihood as described by
Oppe and van Hout (2010) <doi:10.1002/hec.3560> and Ramos-Goñi et al. (2017) <doi:10.1097/MLR.0000000000000283>.
The package is based on 'flexmix' and among others contains an M-step-driver as described by Leisch (2004) <doi:10.18637/jss.v011.i08>.
Users can estimate latent classes and address preference heterogeneity. Both uncensored and censored data are supported.
Furthermore, heteroscedasticity can be taken into account. It is possible to control for different covariates on the continuous and dichotomous parts of the data and start values can differ
between the expected latent classes.

Svenja Elkenkamp

hyreg2

Estimate Latent Classes on a Mixture of Continuous and
Dichotomous Data

Kim Rand

John Grosser

EuroQol 

simulated_data_norm function

<div class="section" id="simulated-data-norm">
<h3><code>simulated_data_norm</code></h3>
A simulated data frame with 600 rows and 9 columns, following a combination of normal and binomial distribution<dl>
<dt>type</dt>
<dd>type of data, "TTO" indicates normal distribution, "DCE_A" indicates binomial distribution</dd><dt>y</dt>
<dd>result of the formula y ~ x1 + x2 + x3</dd><dt>x1, x2, x3</dt>
<dd>random numbers from rnorm</dd><dt>class</dt>
<dd>original class of the data point</dd><dt>id</dt>
<dd>id number of observations to simulated different persons</dd><dt>y_non</dt>
<dd>result of the formula y ~ (x1 \* beta1 + x2 \* beta3) \* (x1 \* beta1 + x3 \* beta3)</dd><dt>y_cens</dt>
<dd>column y censored at 3</dd>...</dl></div>

Format

simulated_data_norm — simulated_data_norm

<div class='section' id='simulated-data-norm'>
<h3><code>simulated_data_norm</code></h3>


A simulated data frame with 600 rows and 9 columns, following a combination of normal and binomial distribution<dl>
<dt>type</dt>
<dd>type of data, "TTO" indicates normal distribution, "DCE_A" indicates binomial distribution</dd>

<dt>y</dt>
<dd>result of the formula y ~ x1 + x2 + x3</dd>

<dt>x1, x2, x3</dt>
<dd>random numbers from rnorm</dd>

<dt>class</dt>
<dd>original class of the data point</dd>

<dt>id</dt>
<dd>id number of observations to simulated different persons</dd>

<dt>y_non</dt>
<dd>result of the formula y ~ (x1 \* beta1 + x2 \* beta3) \* (x1 \* beta1 + x3 \* beta3)</dd>

<dt>y_cens</dt>
<dd>column y censored at 3</dd>

...

</dl>

</div>

simulated_data_norm: simulated_data_norm

Description

Usage

Arguments

Format

`simulated_data_norm`