forgnlit30c

<p>This data set contains, on a county level, the proportion of white residents
ten years and older who are foreign born, and the proportion of those
residents who are literate.  Data come from the 1930 census and were first
analyzed by Robinson (1950). Counties with fewer than 100 foreign born
residents are dropped.</p>

datasets

Implements the Bayesian and likelihood methods proposed
in Imai, Lu, and Strauss (2008 <DOI: 10.1093/pan/mpm017>) and
(2011 <DOI:10.18637/jss.v042.i05>) for ecological inference in 2
by 2 tables as well as the method of bounds introduced by Duncan and
Davis (1953).  The package fits both parametric and nonparametric
models using either the Expectation-Maximization algorithms (for
likelihood models) or the Markov chain Monte Carlo algorithms (for
Bayesian models).  For all models, the individual-level data can be
directly incorporated into the estimation whenever such data are available.
Along with in-sample and out-of-sample predictions, the package also
provides a functionality which allows one to quantify the effect of data
aggregation on parameter estimation and hypothesis testing under the
parametric likelihood models.

Ying Lu

Ecological Inference in 2x2 Tables

Kosuke Imai

Aaron Strauss

Hubert Jin

forgnlit30c function

<p>A data frame containing 6 variables and 1976 observations</p><table class="table">
<tr><td>X</td><td>numeric</td><td>proportion of the white population at
least 10 years of age that is foreign born</td></tr>
<tr><td>Y</td><td>numeric</td><td>proportion of the white population at least 10 years of age that is
illiterate</td></tr>
<tr><td>W1</td><td>numeric</td><td>proportion of the foreign-born white
population at least 10 years of age that is illiterate</td></tr>
<tr><td>W2</td><td>numeric</td><td>proportion of the native-born white population at least 10 years of age
that is illiterate</td></tr>
<tr><td>state</td><td>numeric</td><td>the ICPSR state code</td></tr>
<tr><td>county</td><td>numeric</td><td>the ICPSR (within state) county code</td></tr>
</table><p></p><p></p>

Format

Foreign-born literacy in 1930, County Level — forgnlit30c

<p>A data frame containing 6 variables and 1976 observations</p><table class='table'>
<tr><td>X</td><td>numeric</td><td>proportion of the white population at
least 10 years of age that is foreign born</td></tr>
<tr><td>Y</td><td>numeric</td><td>proportion of the white population at least 10 years of age that is
illiterate</td></tr>
<tr><td>W1</td><td>numeric</td><td>proportion of the foreign-born white
population at least 10 years of age that is illiterate</td></tr>
<tr><td>W2</td><td>numeric</td><td>proportion of the native-born white population at least 10 years of age
that is illiterate</td></tr>
<tr><td>state</td><td>numeric</td><td>the ICPSR state code</td></tr>
<tr><td>county</td><td>numeric</td><td>the ICPSR (within state) county code</td></tr>
</table>



forgnlit30c: Foreign-born literacy in 1930, County Level

Description

Arguments

Format

References

X	numeric	proportion of the white population at least 10 years of age that is foreign born
Y	numeric	proportion of the white population at least 10 years of age that is illiterate
W1	numeric	proportion of the foreign-born white population at least 10 years of age that is illiterate
W2	numeric	proportion of the native-born white population at least 10 years of age that is illiterate
state	numeric	the ICPSR state code
county	numeric	the ICPSR (within state) county code