model_list

<code>model_list()</code> generates an exhaustive list of lme4 model formulas from
the individual level and context level variables as well as geographic unit
variables to be iterated over in best subset selection.

A tool that improves the prediction performance of multilevel
regression with post-stratification (MrP) by combining a number of machine
learning methods. For information on the method, please refer to Broniecki,
Wüest, Leemann (2020) ''Improving Multilevel Regression with
Post-Stratification Through Machine Learning (autoMrP)'' in the
'Journal of Politics'. Final pre-print version:
<https://lucasleemann.files.wordpress.com/2020/07/automrp-r2pa.pdf>.

Philipp Broniecki

autoMrP

Improving MrP with Ensemble Learning

Reto Wüest

Lucas Leemann

Florian Schaffner

Hadley Wickham

model_list function

<dl><dt>y</dt>
<dd>Outcome variable. A character vector containing the column names of
the outcome variable.</dd>
<dt>L1.x</dt>
<dd>Individual-level covariates. A character vector containing the
column names of the individual-level variables in <code>survey</code> and
<code>census</code> used to predict outcome <code>y</code>. Note that geographic unit
is specified in argument <code>L2.unit</code>.</dd>
<dt>L2.x</dt>
<dd>Context-level covariates. A character vector containing the
column names of the context-level variables in <code>survey</code> and
<code>census</code> used to predict outcome <code>y</code>.</dd>
<dt>L2.unit</dt>
<dd>Geographic unit. A character scalar containing the column name
of the geographic unit in <code>survey</code> and <code>census</code> at which outcomes
should be aggregated.</dd>
<dt>L2.reg</dt>
<dd>Geographic region. A character scalar containing the column
name of the geographic region in <code>survey</code> and <code>census</code> by which
geographic units are grouped (<code>L2.unit</code> must be nested within
<code>L2.reg</code>). Default is <code>NULL</code>.</dd></dl>

Arguments

A list of models for the best subset selection. — model_list

<dl>

<dt>y</dt>
<dd>Outcome variable. A character vector containing the column names of
the outcome variable.</dd>


<dt>L1.x</dt>
<dd>Individual-level covariates. A character vector containing the
column names of the individual-level variables in <code>survey</code> and
<code>census</code> used to predict outcome <code>y</code>. Note that geographic unit
is specified in argument <code>L2.unit</code>.</dd>


<dt>L2.x</dt>
<dd>Context-level covariates. A character vector containing the
column names of the context-level variables in <code>survey</code> and
<code>census</code> used to predict outcome <code>y</code>.</dd>


<dt>L2.unit</dt>
<dd>Geographic unit. A character scalar containing the column name
of the geographic unit in <code>survey</code> and <code>census</code> at which outcomes
should be aggregated.</dd>


<dt>L2.reg</dt>
<dd>Geographic region. A character scalar containing the column
name of the geographic region in <code>survey</code> and <code>census</code> by which
geographic units are grouped (<code>L2.unit</code> must be nested within
<code>L2.reg</code>). Default is <code>NULL</code>.</dd>

</dl>

model_list: A list of models for the best subset selection.

Description

Usage

Value

Arguments