Week 10 Assignment Guidance – Regression

1. Import the file from Excel called "Hospital Regression Data" into SPSS . This file represents n=67 hospitals in your region from the year 2003. There are ten variables in this file and they are all coded as continuous. These variables are: TotalERVisits , TotalExp , AverageMonthlyBedDays , Dispositions , TotalVisits , Admissions , SurgicalVisits , AssignedAdminFTEs , CaseMix and Births .
2. Your research Question is: "What factors are affecting Total Expenditures in my Facility?" A follow on research question might be, "Once I have identified variables affecting costs in my facility, how do I prioritize resources to affect those items that most influence costs in my facility?"
3. Before you begin your analysis, run a histogram (univariate analysis and/or descriptive analysis) on all the variables. Which ones meet the assumptions of regression analysis – which ones do not?
   1. *** NOTE: You will see that there is/are MISSING data for all the variables. We have not covered missing data yet – as a result – for this exercise PLEASE IGNORE all missing data and run the analysis on the variables as they are given to you.
4. Run a regression analysis with TOTALExp as your DV and all others as your IVs. Examine your regression output for those significant findings covered in the lecture
5. Write a 1-2 page ( MAX ) report on the output. You may include your SPSS output as attachments. You may also attach your SPSS output as a PDF file with hand written notes on the output if you want.
6. Your written MS Word report should include an analysis of – and a presentation of – the following:
   1. A presentation of the research question.
   2. An overview of the Null and Alternate Regression hypothesis
   3. Write out the initial regression equation as it pertains to your variables. Give a short 1-2 paragraph explanation of the regression equation
   4. A presentation of – and an analysis of – the following based on SPSS output:
      1. Descriptive statistics
      2. Correlation tables
      3. Model Summary table
      4. Coefficients
      5. Collinearity diagnostics
      6. Your presentation of the equation for solving the regression equation
   5. Describe your overall thoughts and decision making options with the model.
7. This does not have to be a full blown written report. You may write bulleted answers to the above questions.
8. OPTIONAL: ENTIRELY for EXTRA CREDIT: 1 point
   1. Make decisions on missing data and retool the variables – why did you make the decisions you did?
      1. HINT: basic options are MEAN SUBSTITUTION (substituting all missing values for the mean of that variable) – or – ELIMINATION (eliminating the entire case with any missing data from the analysis). This will decrease your sample size, but may provide a better model.
   2. Based on your retooled variables, rerun the model – what major differences do you see? Discuss

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Solution: The downloadable solution consists of 14 pages, 748 words and 9 charts.
Deliverable: Word Document