Reference no: EM132388221

Analysis Assignment -

Purpose: To assess skills in data management and statistical analysis using regression.

This assignment uses the course data file that each student created at Immersion. Even though the data are from a real-life survey, this assignment requires you to approach the data as if it were data from your own clinical scholarly project as described in the following scenario. Each response should be clear and concise, using graduate-level writing, complete sentences, and respond to the question directly.

Scenario for Analysis -

You, the intrepid DNP student, are excited about the preliminary findings from your CSP analysis. However, your demanding advisor, Dr. Abby Normal, wants you to dig a little deeper. For this assignment you will evaluate three research questions using a chi-square test and linear regression based on the following variables of interest: bmi_change, sessions, gender, race, age, married, alcohol. You may wish to draw on the results of your prior analyses to fully respond to these questions.

RQ1: Is there a relationship between the change in patient BMI (bmi_change) and the number of program sessions attended (sessions)?

RQ2: Is there a difference in alcohol consumption among married patients in the sample?

Step 1: Open your Course SPSS data file.

Step 2: (SPSS Output) Run the following statistics:

To confirm the work is your own, first display the data file information in SPSS by going to File, Display Data File Information, Working File before beginning your analysis.

Prepare for this analysis by creating dummy variables for gender and race.

Frequency table of bmi_change with a report of the mean and standard deviation.

Histogram of bmi_change with normal curve.

Crosstab of married (rows) vs. alcohol (columns)

• Select "Exact" with a 5-minute time limit under Exact - omit.
• Select "Chi-square" and "McNemar" statistics under Statistics.
• Select Row Percentages under Cells.

Scatterplot of sessions (x) and bmi_change (y) with a regression line.

Build four regression models separately (do not use blocks):

• Model 1: Linear regression of bmi_change (dependent) on sessions (independent).
• Model 2: Linear regression of bmi_change (dependent) on sessions while controlling for gender (independents).
• Model 3: Linear regression of bmi_change (dependent) on sessions while controlling for gender and race (independents).
• Model 4 (Final model): Linear regression of bmi_change (dependent) on sessions while controlling for gender, race, and age (independents).

Save the SPSS output file to a place on your computer where you can find it again.

• Name the file with your last name, the assignment number, the file type, and the date.
• Using the format Lastname3_Output_MMDDYYYY.

Step 3: Respond to the following questions. Your responses should follow APA formatting guidelines (e.g., double-spaced, referenced, etc.)

1. In your own words, describe the variables of interest. In your description, make sure to include at least one measure of central tendency and one measure of variation. Your descriptions should be substantive sentences describing your data beyond simply reporting descriptive statistics.

2. Create two APA tables: one for your chi-square test and one for your regression analysis.

3. Draw conclusions about RQ1 based on the analysis you conducted. Address the following for each regression:

a. Write the final regression model and the final fitted regression model.

b. Provide a substantive interpretation of the slope and main intercept of interest in the first (simple) regression model and the final regression model.

c. Is there a statistically significant relationship in the final model? Explain using two statistics from your analysis that support your claim.

d. How does the relationship change from the simple model to the final model as predictors are added?

e. Make a prediction from the final fitted model.

f. Interpret the R-square statistic in the final model.

g. How did the R-square change from the first model to the final model as additional predictors were added? What does this tell us about the models?

h. Discuss other factors that could influence the outcome.

i. Is there a clinically significant relationship between sessions attended and the change in BMI?

4. Draw conclusions about RQ 2 based on the analysis you conducted. Address the following:

a. What Chi-square test is being used?

b. What are the assumptions of the Chi-Square test?

c. Interpret the results (use Frankie, et. al., as a guide).

d. Are the "results statistically significant?

e. Are the results clinically significant and is there a reason to be concerned about alcohol consumption among married and unmarried participants in the study?

f. What other analysis could be done using data from your data set to further investigate this question?

5. Prepare a brief memo for your CSP chair, Dr. Abby Normal, summarizing the findings of your analysis and proposing a direction for further evaluation. Use statistical jargon sparingly and, when you do, explain what you mean. Focus on substantive interpretation supported by APA format statistics.

6. Save the file using the format: Lastname3_Analysis_MMDDYYY.

Step 5: Submit your 2 files for grading.

Attachment:- Analysis Assignment Files.rar