welfare2

A dataset containing simulated data about public opinion in different
countries

datasets

Implementation of MCMC algorithms to estimate the Hierarchical Dirichlet Process Generalized Linear Model (hdpGLM) presented in the paper Ferrari (2020) Modeling Context-Dependent Latent Heterogeneity, Political Analysis <DOI:10.1017/pan.2019.13> and <doi:10.18637/jss.v107.i10>.

Diogo Ferrari

hdpGLM

Hierarchical Dirichlet Process Generalized Linear Models

welfare2 function

A data frame with 2000 rows and 6 variables:<dl>
 <dt>support</dt>
<dd>support for welfare policies</dd> <dt>inequality</dt>
<dd>levels of inequality in the neighborhood</dd> <dt>income</dt>
<dd>individual-level income</dd> <dt>ideology</dt>
<dd>individual-level ideology</dd> <dt>country</dt>
<dd>country label or index</dd> <dt>gap</dt>
<dd>country-level gender gap in country's provision of public good</dd>
</dl>

Format

Fake data set with 2000 observations — welfare2

A data frame with 2000 rows and 6 variables:<dl>
 <dt>support</dt>
<dd>support for welfare policies</dd>

 <dt>inequality</dt>
<dd>levels of inequality in the neighborhood</dd>

 <dt>income</dt>
<dd>individual-level income</dd>

 <dt>ideology</dt>
<dd>individual-level ideology</dd>

 <dt>country</dt>
<dd>country label or index</dd>

 <dt>gap</dt>
<dd>country-level gender gap in country's provision of public good</dd>


</dl>

welfare2: Fake data set with 2000 observations

Description

Usage

Arguments

Format