Activity 10: MANOVA and Reflection
4Comparison of Multiple Outcome Variables
This activity introduces you to a very common technique - MANOVA. MANOVA is simply an extension of an ANOVA and allows for the comparison of multiple outcome variables (again, a very common situation in research and what luck that instead of have to perform a series of analysis one MANOVA can do it all for you!).
In this activity you will also reflect on all the knowledge you have gained over your time in this course, and final take an ungraded post test. The post test is NCU's way of assessing how well the course did in teaching you and your fellow doctoral Learners the core competencies in statistics. So, while the test is not graded, please take your time and do your best.
To Prepare for Activity 10:
NOTE: You may experience an error message when attempting to run the analysis using SPSS of the .sav file used in this assignment. The error message says:
If you experience this error, click on the data view tab of the opened .sav file, then click on the line separating the labels of the first and second column. Drag the width of the first column out approximately 25% from its initial width. Save the file. The analysis should now work as intended.
Read Chapter 16 in the text. It will be to your advantage to have SPSS open on your computer as you work through chapter 16. While you are reading consider your area of research interest and when you have seen a MANOVA framework applied. How might you use these analytical strategies in your dissertation research?
Optional Preparation for Activity 10
After completing the above activities, if you feel you need additional instruction on the concepts covered, please choose from any of the following activities that will assist you in mastering the core concepts.
Activity 10
You will submit one Word document for this activity. You will create this Word document by cutting and pasting SPSS output into word.
Part A. SPSS Activity
In this exercise, you are playing the role of a researcher that is testing new medication designed to improve cholesterol levels. When examining cholesterol in clinical settings, we look at two numbers: low-density lipoprotein (LDL) and high-density lipoprotein (HDL). You may have heard these called "good" (HDL) and "bad" (LDL) cholesterol. For LDL, lower numbers are better (below 100 is considered optimal. For HDL, 60 or higher is optimal.
In this experiment, the researcher is testing three different versions of the new medication. In data file "Activity 10.sav" you will find the following variables: group (0=control, 1=Drug A, 2=Drug B, 3=Drug C), LDL, and HDL (cholesterol numbers of participants after 12 weeks).
Using a MANOVA, try to ascertain which version of the drug (A, B or C) shows the most promise. Perform the following analyses, and paste the SPSS output into your document.
1. Exploratory Data Analysis.
a. Perform exploratory data analysis on the relevant variables in the dataset. When possible, include appropriate graphs to help illustrate the dataset.
b. Give a one to two paragraph write up of the data once you have done this.
c. Create an APA style table that presents descriptive statistics for the sample.
2. Perform a MANOVA. Using the "Activity 10.sav" data set perform a MANOVA. "Group" is your fixed factor, and LDL and HDL are your dependent variables. Be sure to include simple contrasts to distinguish between the drugs (group variable). In the same analysis, include descriptive statistics, and parameter estimates. Finally, be certain to inform SPSS that you want post-hoc test to help you determine which drug works test best.
a. Is there any statistically significant difference in how the drugs perform? If so, explain the effect. Use the post hoc tests as needed.
b. Write up the results using APA style and interpret them.
Part B. Reflection
Reflect on your experience throughout the course. In your Activity #10 document, include a brief assessment of what you have learned. In 2-3 paragraphs, cover the following:
1. What were the three most important things you learned?
2. How will the material in this course help you in your dissertation work?
3. What would you like to have seen covered that wasn't?
Submit your files in the Course Work area below the Activity screen.
Learning Outcomes: 3, 4, 5, 6, 10, 11
Calculate, integrate, and evaluate descriptive statistical analysis.
Create, integrate, and evaluate visual displays of data.
Apply appropriate statistical tests based on level of measurement.
Calculate, interpret, and understand the appropriate use of inferential statistical analysis. Evaluate the results of the analysis.
Demonstrate proficiency in the use of SPSS.
Demonstrate proficiency in reporting statistical output in APA format.