Housekeeping

Introduction

You will analyze this data across two labs. This first lab is an individual lab and each student must submit a separate preliminary report by the due date. In the next lab, you will work within your teams and submit one final report by that due date.

The Data

We will consider data from the Centers for Medicare and Medicaid Services on hospital costs and profit from the 2014 fiscal year. Our interest is in examining variability of net hospital income across states.

One primary item of interest is the ranking of states by net income of hospitals.

It is important to control for the potential influence of hospital ownership (in the variable called control) and of the number of beds (a proxy for hospital size). The ownership categories include Voluntary Nonprofit-Church, Voluntary Nonprofit-Other, Proprietary-Individual, Proprietary-Corporation, Proprietary-Partnership, Proprietary-Other, Governmental-Federal, Governmental-City-County, Governmental-County, Governmental-State, Governmental-Hospital District, Governmental-City, and Governmental-Other.

Exercises

For this lab, ignore potential effects of number of beds and ownership of the hospital. Develop and fit a random effects anova model for netincome (your response variable) using state as your grouping variable. Obtain preliminary results on the rankings of the states.

There will be a page limit on your final report next week but there is NO page limit for this preliminary report. Your preliminary report should include the following.

• Clear specification of your model (using equations and the right notations).
• Clearly-labeled tables and graphical displays describing the data and communicating your findings.
• Uncertainty quantification around effect estimates of interest (no point estimates without uncertainty!).
• Clear description of results in language accessible to a general scientifically-savvy reader.

DO NOT INCLUDE R CODE OR OUTPUT IN YOUR REPORTS. All R outputs should be converted to nicely formatted tables. Feel free to use R packages such as kable, xtable, stargazer, etc.