Multiple Regression Using SPSS:
A cancer specialist from the Los Angeles County General Hospital (LACGH) rated patient optimism in 20 to 40 year old patients with incurable cancer in 1970. In 1990, theresearcher examined hospital records to gather the following:
• SES (1-7)
• Age in 1970
• Optimism in 1970 (1-100)
• Longevity (years lived after the 1970 diagnosis)
Years Lived after Diagnosis is the Dependent Variable.
Use the others (age, optimism, and SES) as the independent variables.
You will also be analyzing multicollinearity in the model and interpreting the model. Be sure to describe which of the model building methods you use.
Requirements
· SPSS software required (version 19 or later). Log and tables must be submitted with assignment
· Each response must contain a detailed written explanation (at least 4-6 sentences) along with the correct answer. Please note that some answers may require more than 4-6 sentences depending on the complexity of the analysis for the answer. Yes/No answers are not sufficient.
· There may be several different sub-analyses required in order to complete the entire analytic procedure
· If there is a significant interaction effect, all possible simple effects must also be conducted
· The results section should conform to generally accepted formatting for statistical results analysis. Example provided
· Must be plagiarism free
· Delivery document should be in a Microsoft Word format using APA style for citing references
Assignment
1. Do the IVs correlate statistically significantly and practically with the DV?
2. Is collinearity a concern among the independent variables?
3. What is the R and adjusted R Square for all IVs entered simultaneously?
4. What variable(s) provide a significant unique contribution(s)?
5. Compose a Results section for this statistical analysis.
6. Compose a Results section for this simple regression.
