testing to Find Relationships Among Many Variables
Both multiple regression and logistic regression testing are used to evaluate the relative predictive contribution of each of several independent variables on a dependent variable. When the researcher, using common sense and evidence from the literature, selects a narrow set of independent variables that she or he believes are important or useful in predicting an outcome (dependent variable), it is said that a predictive model is being created to explain the phenomena being studied.
You are encouraged to review the multiple and logistic regression materials from previous units. Then, review How to Choose a Statistical Test and the test-selection tutorials linked in the Resources to determine which test is most likely to be appropriate for your data type.
Using SPSS and the Framingham study data set, perform and interpret statistical tests that answer the following research questions. Then, provide a written analysis of your results.
- Demonstrate how baseline BMI, age, and gender (variables: bmi1, age1, sex1) can be used to predict baseline glucose (variable: glucose1).
- How do baseline glucose, cholesterol, systolic blood pressure, and BMI (variables: glucose1, totchol1, sysbp1, and bmi1) affect the likelihood that a participant will have coronary heart disease by the time of the third examination (variable: prevchd3)?
Written Analysis Format and Length
Format your analysis using APA style.
- Use the APA Style Paper Template, linked in the Resources. An APA Style Paper Tutorial is also provided to help you in writing and formatting your analysis.
- Your analysis should be 2–3 pages in length, not including the title page and references page.
Note: The requirements outlined below correspond to the grading criteria in the scoring guide. Be sure that your statistical analysis addresses each point, at a minimum. You may also want to read the scoring guide to better understand how each criterion will be assessed.
- Perform the appropriate statistical tests (based on the assumption test).
- Provide your rationale for test selection.
- Interpret the results of your statistical tests for each research question.
- Consider associated caveats and limitations.
- Determine the practical, public health-related implications of your statistical tests.
- What evidence do you have that validates your conclusions?
- Explain how either multiple or logistic regression statistical techniques might be used to understand a complex system in public health.
- Provide a 1–2-paragraph explanation, with 1–2 supporting references.
- Write clearly and concisely, using correct grammar, mechanics, and APA formatting.
- Write for an academic audience, using appropriate statistical terminology, style, and form.
- Express your main points and conclusions coherently.
- Proofread your writing to minimize errors that could distract readers and make it more difficult for them to focus on the substance of your statistical analysis.
Submit appropriately labeled SPSS results output files (.spv), along with your written analysis.
Include the test results and associated graphic in your written analysis (copied from the output file and pasted into a Word document). Refer to How to Copy SPSS Output and Paste It Into a Word Document, linked in the Resources.