ict.hausman.test

Hausman Specification Test for Two List Experiment Regression Fit Objects

Allows researchers to conduct multivariate
statistical analyses of survey data with list experiments. This
survey methodology is also known as the item count technique or
the unmatched count technique and is an alternative to the commonly
used randomized response method. The package implements the methods
developed by Imai (2011) <doi:10.1198/jasa.2011.ap10415>,
Blair and Imai (2012) <doi:10.1093/pan/mpr048>,
Blair, Imai, and Lyall (2013) <doi:10.1111/ajps.12086>,
Imai, Park, and Greene (2014) <doi:10.1093/pan/mpu017>,
Aronow, Coppock, Crawford, and Green (2015) <doi:10.1093/jssam/smu023>,
Chou, Imai, and Rosenfeld (2017) <doi:10.1177/0049124117729711>, and
Blair, Chou, and Imai (2018) <https://imai.fas.harvard.edu/research/files/listerror.pdf>.
This includes a Bayesian MCMC implementation of regression for the
standard and multiple sensitive item list experiment designs and a
random effects setup, a Bayesian MCMC hierarchical regression model
with up to three hierarchical groups, the combined list experiment
and endorsement experiment regression model, a joint model of the
list experiment that enables the analysis of the list experiment as
a predictor in outcome regression models, a method for combining
list experiments with direct questions, and methods for diagnosing and
adjusting for response error. In addition, the package implements the
statistical test that is designed to detect certain failures of list
experiments, and a placebo test for the list experiment using data from
direct questions.

Graeme Blair

list

Statistical Methods for the Item Count Technique and List
Experiment

Winston Chou

Kosuke Imai

Bethany Park

Alexander Coppock

ict.hausman.test function

<dl><dt>ml</dt>
<dd>Maximum likelihood model fit, for example from ictreg(method = "ml")</dd>
<dt>nls</dt>
<dd>NLS model fit, for example from ictreg(method = "nls")</dd>
<dt>abs</dt>
<dd>Flag to override error when Hausman statistic is negative, which may indicate misspecification. Set to <code>FALSE</code> to override.</dd>
<dt>psd</dt>
<dd>Flag to override error when variance-covariance difference is non-positive semidefinite, suggesting misspecification. Set to <code>TRUE</code> to override.</dd></dl>

Arguments

Hausman Specification Test for Two List Experiment Regression Fit Objects — ict.hausman.test

<dl>

<dt>ml</dt>
<dd>Maximum likelihood model fit, for example from ictreg(method = "ml")</dd>


<dt>nls</dt>
<dd>NLS model fit, for example from ictreg(method = "nls")</dd>


<dt>abs</dt>
<dd>Flag to override error when Hausman statistic is negative, which may indicate misspecification. Set to <code>FALSE</code> to override.</dd>


<dt>psd</dt>
<dd>Flag to override error when variance-covariance difference is non-positive semidefinite, suggesting misspecification. Set to <code>TRUE</code> to override.</dd>

</dl>

ict.hausman.test: Hausman Specification Test for Two List Experiment Regression Fit Objects

Description

Usage

Value

Arguments