hospital_prepared

A data set containing simulated and processed readmissions data for 500 hospitals with
three continuous covariates. This is the form of the data needed to use <code>fe.prov</code>.

datasets

A structured profile likelihood algorithm for the logistic fixed effects model and an approximate expectation maximization (EM) algorithm for the logistic mixed effects model. Based on He, K., Kalbfleisch, J.D., Li, Y. and Li, Y. (2013) <doi:10.1007/s10985-013-9264-6>.

Michael Kleinsasser

FEprovideR

Fixed Effects Logistic Model with High-Dimensional Parameters

Kevin(Zhi) He

Wenbo Wu

hospital_prepared function

A <code>data.frame</code> with 24438 rows and 8 variables (columns):<dl class="dl-horizontal">
<dt>Y</dt><dd>Indicator for readmission; 1=Yes, 0=No; numeric</dd>
<dt>prov.ID</dt><dd>Provider ID; numeric</dd>
<dt>z1</dt><dd>Simulated covariate 1, numeric</dd>
<dt>z2</dt><dd>Simulated covariate 2, numeric</dd>
<dt>z3</dt><dd>Simulated covariate 3, numeric</dd>
<dt>included</dt><dd>variable 'included' as an indicator</dd>
<dt>no.readm</dt><dd>providers with no readmission within 30 days</dd>
<dt>all.readm</dt><dd>providers with all readmissions within 30 days</dd>
</dl>

Format

Prepared version of simulated readmissions data for 500 hospitals — hospital_prepared

A <code>data.frame</code> with 24438 rows and 8 variables (columns):<dl class='dl-horizontal'>
<dt>Y</dt><dd>Indicator for readmission; 1=Yes, 0=No; numeric</dd>
<dt>prov.ID</dt><dd>Provider ID; numeric</dd>
<dt>z1</dt><dd>Simulated covariate 1, numeric</dd>
<dt>z2</dt><dd>Simulated covariate 2, numeric</dd>
<dt>z3</dt><dd>Simulated covariate 3, numeric</dd>
<dt>included</dt><dd>variable 'included' as an indicator</dd>
<dt>no.readm</dt><dd>providers with no readmission within 30 days</dd>
<dt>all.readm</dt><dd>providers with all readmissions within 30 days</dd>
</dl>

hospital_prepared: Prepared version of simulated readmissions data for 500 hospitals

Description

Usage

Arguments

Format