covid

<p>A county level COVID-19 dataset in US. It is of interest to examine the association between several county-level characteristics and the cumulative numbers of confirmed cases and deaths. County-level characteristics are based on the 2018 ACS 5-year estimates.</p>

Provides a class of Bayesian beta regression models for the analysis of continuous data with support restricted to an unknown finite support. The response variable is modeled using a four-parameter beta distribution with the mean or mode parameter depending linearly on covariates through a link function. When the response support is known to be (0,1), the above class of models reduce to traditional (0,1) supported beta regression models. Model choice is carried out via the logarithm of the pseudo marginal likelihood (LPML), the deviance information criterion (DIC), and the Watanabe-Akaike information criterion (WAIC). See Zhou and Huang (2022) <doi:10.1016/j.csda.2021.107345>.

Haiming Zhou

betaBayes

Bayesian Beta Regression

Xianzheng Huang

covid function

<p></p><table><tr><td>
    FIPS:</td>
<td> FIPS county code</td>
</tr><tr><td>
    PopE:</td>
<td> total population </td>
</tr><tr><td>
    MaleP: </td>
<td> percentage of people who are male </td>
</tr><tr><td>
    WhiteP: </td>
<td> percentage of people who are white </td>
</tr><tr><td>
    BlackP:</td>
<td> percentage of people who are black or African American</td>
</tr><tr><td>
    Age65plusP:</td>
<td>  percentage of people who are 65 years and over</td>
</tr><tr><td>
    PovertyP:</td>
<td> percentage of people whose income in the past 12 months is below poverty </td>
</tr><tr><td>
    RUCC_2013:</td>
<td> 2013 Rural Urban Continuum Code, with a higher value indicating a more rural county</td>
</tr><tr><td>
    State:</td>
<td> two-letter state abbreviation code </td>
</tr><tr><td>
    deaths: </td>
<td> cumulative number of deaths as of October 13, 2020 </td>
</tr><tr><td>
    cases: </td>
<td> cumulative number of confirmed cases as of October 13, 2020 </td>
</tr></table>

covid: COVID-19 County Level Data

Description

Usage

Arguments

Format

Examples

FIPS:	FIPS county code
PopE:	total population
MaleP:	percentage of people who are male
WhiteP:	percentage of people who are white
BlackP:	percentage of people who are black or African American
Age65plusP:	percentage of people who are 65 years and over
PovertyP:	percentage of people whose income in the past 12 months is below poverty
RUCC_2013:	2013 Rural Urban Continuum Code, with a higher value indicating a more rural county
State:	two-letter state abbreviation code
deaths:	cumulative number of deaths as of October 13, 2020
cases:	cumulative number of confirmed cases as of October 13, 2020