Analyzing Depression Treatment Effectiveness Using StatCrunch

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Progress Check
Use this activity to assess whether you and your peers can: Use StatCrunch to create the appropriate visual display.
Use StatCrunch to create the appropriate numerical summaries.
Use the appropriate variables to analyze the data and answer the questions we are investigating.
Use the appropriate visual display to summarize the data.
Use the appropriate numerical summaries to analyze the data.
Use appropriate statistical vocabulary to analyze the data and answer the questions we are investigating.
Directions my account statcrunch username Aiyah Abdullah password Abdullah_2008
Use the drop-down menu to learn about the three steps needed to complete this assignment.
Three steps to complete the assignment
Context
Clinical depression is a recurrent illness requiring treatment and often hospitalization. Nearly 50% of people who have an episode of major depression will have a recurrence within 2-3 years. Being able to prevent the recurrence of depression in people who are at risk for the disease would go a long way to alleviate the pain and suffering of patients.
During the 1980s the federal government, through the National Institutes of Health (NIH), sponsored a large clinical trial to evaluate two drugs for depression. There were 3 treatment groups. Patients received either Imipramine (Imip), Lithium (Li), or a Placebo (Pl). Researchers randomly assigned patients to one of the 3 treatment groups and followed them for 2-4 years to track any recurrences of depression.
(Prien et al., Archives of General Psychiatry, 1984).
Variables
Hospt: Which hospital the patient was from: Labeled 1, 2, 3, 5 or 6
Treat: 0=Lithium; 1=Imipramine; 2=Placebo
Outcome: 0=Success 1=Failure (recurrence of depression)
Time: Number of weeks until a recurrence (if outcome=1) or until study ended (if outcome=0)
AcuteT: How long the patient was depressed before the start of the current study, measured in days
Age: Age in years
Gender: 1=Female 2=Male
Data
If you have not already done so, open the depression data set in the Stats at Cuyamaca College group on StatCrunch (directions – opens in a new tab).
Prompt
We will analyze the data to answer the second research question: Which of the drugs (if either) delayed the recurrence of depression longer relative to the placebo? In the previous lab-preparation activity, we identified Treat as the explanatory variable and Time as the response variable. We also determined that we will analyze the data using side-by-side boxplots and descriptive statistics (i.e. 5-number summaries since the graphs are boxplots).
Make graphs and tables:Use StatCrunch to produce side-by-side boxplots. (directions)
Embed your graphs into the textbox, and be sure to include the Alt Text. To recall how to embed a picture into a textbox, see the StatCrunch directions below.
Use StatCrunch to produce the descriptive statistics (a single table containing the 5-number summaries for each comparison group). (directions)
Copy and paste the StatCrunch output table into the textbox. Analyze the data: Compare the distributions for the treatment groups as demonstrated in Unit 2. For example, compare medians and intervals of typical values. Describe the shape and any outliers. Be sure to write your comparisons so the reader can understand the context of the numbers. For example, don’t just say the median is 30; instead, say something like this: on average patients taking the placebo relapsed in 30 days (Q2=30 days).
Draw a conclusion: What can we conclude from your analysis? Did one drug successfully delay a relapse of depression better than the others? What evidence supports your conclusion?
Summarize your conclusions in response to both research questions: In this lab, you compared three treatments (two drugs and the placebo) using two different variables. In Part 1 you compared whether or not a relapse into depression occurred for each of the two drugs and the placebo. In Part 2 you compared the length of time until the next relapse for the two drugs and the placebo. What can you conclude in light of both analyses? Is one treatment better than the other? How does the data support your conclusion?

🚨 Struggling with where to start this assignment? Follow this guide to tackle your assignment easily! 🚨

This assignment involves using StatCrunch to analyze clinical depression treatment data. You will create visual displays, compute numerical summaries, and interpret statistical findings. Follow this step-by-step guide to complete your work smoothly!

Step 1: Understand the Task

Your objective is to analyze the dataset and determine which drug (if any) was more effective in delaying depression recurrence compared to the placebo. You will:

✔ Create side-by-side boxplots to compare the three treatment groups.
✔ Generate descriptive statistics (5-number summary) for each group.
✔ Interpret the data to compare medians, distributions, and outliers.
✔ Draw a conclusion on whether Imipramine or Lithium was more effective than the placebo.

Step 2: Access the Data in StatCrunch

Log in to StatCrunch using your provided credentials.
Open the depression dataset from the “Stats at Cuyamaca College” group.
Identify the two key variables for this analysis:
- Explanatory Variable: Treat (0=Lithium, 1=Imipramine, 2=Placebo)
- Response Variable: Time (weeks until recurrence of depression or end of study)

Step 3: Generate Visual Displays

A. Create Side-by-Side Boxplots

In StatCrunch, go to Graph → Boxplot.
Select Time as the response variable.
Select Treat as the grouping variable.
Click Compute! to generate the boxplots.
Save and embed the boxplot image into your report, ensuring it has an Alt Text description.

Step 4: Generate Descriptive Statistics (5-Number Summary)

In StatCrunch, go to Stat → Summary Stats → Columns.
Select Time as the response variable.
Select Treat as the grouping variable.
Choose the following statistics:
- Minimum
- Q1 (First Quartile)
- Median (Q2)
- Q3 (Third Quartile)
- Maximum
Click Compute! and copy-paste the output table into your report.

Step 5: Interpret the Data

Now that you have both the boxplots and 5-number summaries, analyze them by comparing:

✔ Medians: Which treatment group had the longest median time before relapse?
✔ Interquartile Ranges (IQRs): Which treatment had the widest spread of typical values?
✔ Outliers: Were there any extreme values in any group?
✔ Overall Shape: Are the distributions symmetric, skewed, or varied?

🔹 Example Interpretation:

Patients on the placebo relapsed in X weeks on average (Median = X).
Patients on Imipramine lasted Y weeks before relapse (Median = Y), showing a longer time to recurrence.
Patients on Lithium had a median relapse time of Z weeks, indicating…

Step 6: Draw Conclusions

Based on your analysis:

✅ Which drug delayed relapse the longest?
✅ Did one drug perform significantly better than the placebo?
✅ What statistical evidence supports your conclusion?

🔹 Example Conclusion:
“Based on the boxplots and summary statistics, patients treated with Imipramine had the longest median time before relapse, suggesting it was the most effective treatment. The placebo group had the shortest median time, confirming that without treatment, relapse occurred sooner. The data supports the effectiveness of Imipramine over both Lithium and placebo.”

Step 7: Final Summary

In your final section, summarize:

✔ Which treatment was best?
✔ How did the time-to-relapse compare across groups?
✔ Does the data support using one drug over another?

Step 8: Review & Submit

✅ Check formatting: Ensure your report has boxplots, a 5-number summary table, and clear interpretations.
✅ Proofread your work for clarity and grammar.
✅ Submit your assignment as required.

🎯 Final Tip:

Use clear statistical vocabulary and describe findings in context (e.g., “Patients on Lithium had a median relapse time of X weeks, which was longer than the placebo but shorter than Imipramine”).

With this step-by-step approach, your assignment will be thorough, well-structured, and easy to follow! 🚀

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