Module 8 – Treating Depression Lab Part 1 (discussion 1) – Mod 8 Group 2

From 2020SP-MATH-160-6897

66 unread replies.66 replies.

Learn by Doing

In this activity, you will investigate the first question related to the study described below.

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.

Here are the directions and grading rubric for the Learn by Doing discussion board exercises.

A list of StatCrunch directions is provided at the bottom of this page.

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 1st research question: Which of the drugs (if either) was more successful in preventing the recurrence of depression relative to the placebo?

In the previous lab-preparation activity, we determined that we will analyze the data using a two-way table and conditional percentages.

1. Use StatCrunch to produce a two-way contingency table. (directions)
   Copy the table in your StatCrunch output window and paste it in your initial discussion post. (directions)
   After you paste the content of the your StatCrunch output window into your discussion post, keep the table titled Contingency table results: and delete the Chi-Square results: table.
2. Analyze the data in your two-way table by finding appropriate conditional percentages. Write each conditional percentage as a ratio (e.g. 25 out of 40) and as a percentage (e.g. 25/40 = 62.5%). Then write a sentence that explains the meaning of the percentage in the context of the research question.
3. Draw a conclusion. Based on this study, which drug was the most effective in preventing the recurrence of depression? Support your conclusion using conditional percentages.

LIST OF STATCRUNCH DIRECTIONS

Each link will open in a new window. To return to this discussion, either close the new tab or select the tab for this discussion.

• Create Your Stats-Class Folder in Canvas (You only need to do this once.)
• Purchase StatCrunch (You only need to do this once.)
• Open StatCrunch
• Download Excel Data File
• Upload Excel Data File to StatCrunch
• Download StatCrunch Output Window (no screenshots; please use these directions)
• Upload Files into Your Stat-Class Folder in Canvas
• Embed Pictures in a Discussion Post (no attachments; please use these directions)
• Create a Two-way Contingency Table with Data
• Copy & Paste a StatCrunch Table

Here is a PDF document with all StatCrunch directions (Links to an external site.).

GRADING

To view the grading rubric for this discussion board, click on menu icon (three vertical dots) and then select show rubric. Please note, if viewing the course via the Canvas mobile app the rubric does not appear on this page.

TIPS FOR SUCCESS

• • • To post your initial post, click the “reply” button at the top of the introduction thread below.
    • You are required to reply to two of your peers in this discussion; don’t forget to complete this requirement of the activity or you will lose points. Provide high-quality feedback to your peers.

___________________________________________________

Learn by Doing Discussions

Directions

Submit your initial post:

• Address all items in the discussion prompt with your initial post (be sure to number your answers clearly).
• If directed to do so, embed all required StatCrunch output in your initial post (do not submit StatCrunch output as an attachment).
• All pertinent StatCrunch directions will be provided in context.
• You were randomly assigned to a group for all discussions in the current module. However, you will not be able to see responses from other students in your group until you post your initial response to the discussion prompt.

Review other responses and reply to self with corrections:

• After you post your initial response, continue to the ANSWER(S) page and review your instructor’s response.
• Return to the discussion and read the responses from others in your group.
• We all learn from mistakes (our own and our classmates’ mistakes). So, please do not correct your mistakes immediately. If possible, wait until you receive feedback from at least one other group member, then reply to your own initial post with your corrections. Please do not create a new thread for your corrections.

Provide high-quality feedback:

• Provide high-quality feedback to two of your group-mates. WARNING: To earn full-credit for the assignment, every student in your group must receive high-quality feedback from at least two distinct group-mates. Keep in mind, that a student’s reply to self with a correct does NOT count as feedback.
• Here is a PDF with the features of high-quality feedback (Links to an external site.).

Grading Rubric

There will be one group grade for all students participating in the group discussion. Those students who do not fully participate will earn a lower score. For example, if you do not commit a good-faith effort to responding to the discussion prompt in your initial post (by the due date), you are not a fully participating group member.

Here are the requirements for the group to earn credit for this discussion. By the due date:

1. Commit a good-faith effort in responding to the above prompt in your initial post.
   1. Your response to the discussion prompt must be based on the reading and Module content.
   2. All of your answers to the prompt must be included in in your initial reply to this discussion.
2. Read ALL initial posts with your group-mates’ responses to the discussion prompt.
3. Make a good-faith effort to provide high quality feedback to at least two different group-mates. The group will earn a higher grade if the feedback helps students make necessary corrections to their initial answers.
4. You must receive high-quality feedback from at least two distinct group-mates.
5. Carefully read all the feedback your group-mates gave you.
6. If necessary, respond to yourself and make corrections to your initial answer(s). Be sure to make corrections in your own words; copying is plagiarism.

USE SAS

The word dox is the requirement and questions.

If you have properly completed your SAS project you will upload the following three items:

1. The DOCX file with the original assignment and rubric (all fields completed).

2. The XLSX file you downloaded with the addition of the tab with the Scatterplots on it and the Regression Output tab for the regression of Price with the three independent variables.

3. A PDF file you produce from SAS that shows the output of your final regression (with a higher R2 than we had with the original model).

please care about plagiarism and follow the instructions .

and help me with management questions .

Select a current research paper (published since 2016) to review. You may select any research paper that is related to Data Science or Big Data Analytics. I strongly recommend that you start your search at Google Scholar (scholar.google.com). Once you enter your search term(s), select the “Since 2016” link on the left. Feel free to choose ANY relevant paper. (I would recommend that you select one that you can read and summarize in a reasonable amount of time. Don’t select a 100 page paper!)

For APA citation information, I have found https://owl.english.purdue.edu/owl/resource/560/01… to be a great resource.

Here is a short list of what I want:

1) Your review should be 1 to 2 pages, single spaced.
2) You should briefly summarize the content of the article or paper and explain how it relates to Data Science and/or Big Data Analytics.
3) IMPORTANT – Provide your own assessment of the article. (Did it make sense? Did you learn anything from it? Do you agree or disagree with the content?)

4) Use the APA style for the paper and any references. You MUST use APA in-text references AND provide a list of any resources you used in the references list at the end of your paper. (PLEASE do NOT overuse references. More than a couple for such a short paper is overkill.)