Some features of this activity may not work well on a cell phone or tablet. We highly recommend that you complete this activity on a computer. Use the rubric at the bottom of this page as a guide for completing this assignment. A list of StatCrunch directions is provided after the Prompt section below. Directions Submit your work: Carefully read all sections below (beginning with the Context section and ending with the Prompt section). Commit a good-faith effort to address all items in the Prompt section below. Please be sure to number your responses. If directed to do so, embed all required StatCrunch output in your initial submission. Please do not submit StatCrunch output as an attachment. Complete your assigned peer reviews: After you submit your initial good-faith attempt, continue to the ANSWER(S) page and review your instructor's response. But please do not submit your corrected work yet. Within three days after the due date, return to this assignment and complete your assigned peer reviews (directions (Links to an external site.)). Submit your corrected work: We all learn from mistakes (our own and our classmates' mistakes). So please do not immediately correct your own mistakes. If possible, wait until you receive feedback from at least one of your peers.  If necessary, correct your work and resubmit the entire assignment - including any required StatCrunch output. Your instructor will only review and grade your most recent submission, so please do not refer to a previous submission. 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 1980's 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 done so already, download the depression datafile (as always, if a login box opens, just close it and then download the file). Then upload the file in StatCrunch.  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 with your initial post.  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 your initial post. 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?

Use the reliability command in SPSS and calculate Chronbac’s Alpha for all variables (Q1 to Q89). What is your calculated value? Is there any way to improve the Chronbac’s Alpha to above 0.8? Explain how.2- Identify the underlying structure between variables Q1 trough Q26, using Factor Analysis with Varimax rotation. Saves the scores using the regression method. Using the eigenvalue criterion of greater than one, how many factors were you able to retain? What is the total variance explained by this model?3- Are the results obtained from the analysis acceptable? Why? Identify the criteria you used to answer this question. What is your best recommendation on improving the results?4- Recode the fpl (poverty status) into a binary variable, fpl_G, with 0 representing families with income levels below 200% of the federal poverty threshold and 1 representing all other families. Use the saved factors from part 2 as the independent variables in a logistic regression using the newly created variable, fpl_G, as the dependent variable. Use the “Enter” method to run this regression. How does this model fit the data? Is the generated model significantly different from a constant only model?

To prepare for this Discussion:Review this week’s Learning Resources and the Descriptive Statistics media program.For additional support, review the Skill Builder: Visual Displays for Categorical Variables and the Skill Builder: Visual Displays for Continuous Variables, which you can find by navigating back to your Blackboard Course Home Page. From there, locate the Skill Builder link in the left navigation pane.Review the Chapter 4 of the Wagner text and the examples in the SPSS software related to central tendency and variability.From the General Social Survey dataset found in this week’s Learning Resources, use the SPSS software and choose one continuous and one categorical variable Note: this dataset will be different from your Assignment dataset).As you review, consider the implications for positive social change based on the results of your data.By Day 3Post, present, and report a descriptive analysis for your variables, specifically noting the following:For your continuous variable:Report the mean, median, and mode.What might be the better measure for central tendency? (i.e., mean, median, or mode) and why?Report the standard deviation.How variable are the data?How would you describe this data?What sort of research question would this variable help answer that might inform social change?Post the following information for your categorical variable:A frequency distribution.An appropriate measure of variation.How variable are the data?How would you describe this data?What sort of research question would this variable help answer that might inform social change?Be sure to support your Main Post and Response Post with reference to the week’s Learning Resources and other scholarly evidence in APA Style.