Hospitals

Information on patient-reported problem rates for 27 teaching hospitals and private academic health centers in the United States.

datasets

Density evaluation and random number generation for the Matrix-Normal Inverse-Wishart (MNIW) distribution, as well as the the Matrix-Normal, Matrix-T, Wishart, and Inverse-Wishart distributions.  Core calculations are implemented in a portable (header-only) C++ library, with matrix manipulations using the 'Eigen' library for linear algebra.  Also provided is a Gibbs sampler for Bayesian inference on a random-effects model with multivariate normal observations.

Martin Lysy

mniw

The Matrix-Normal Inverse-Wishart Distribution

Bryan Yates

Hospitals function

A data frame with 27 rows (one for each hospital) and 4 variables:<dl>
 <dt><code>NSrg</code></dt>
<dd>Non-surgery related problem rate (%).</dd> <dt><code>Srg</code></dt>
<dd>Surgery related problem rate (%).</dd> <dt><code>Severity</code></dt>
<dd>Average health index for surveyed patients.</dd> <dt><code>Size</code></dt>
<dd>Number of patients surveyed.</dd>
</dl>

Format

Hospital profiling data. — Hospitals

A data frame with 27 rows (one for each hospital) and 4 variables:<dl>
 <dt><code>NSrg</code></dt>
<dd>Non-surgery related problem rate (%).</dd>

 <dt><code>Srg</code></dt>
<dd>Surgery related problem rate (%).</dd>

 <dt><code>Severity</code></dt>
<dd>Average health index for surveyed patients.</dd>

 <dt><code>Size</code></dt>
<dd>Number of patients surveyed.</dd>


</dl>

Hospitals: Hospital profiling data.

Description

Usage

Arguments

Format

References