GRADES

Your grade in this class is calculated from your scores on the following items:
Assignment Points
Final Project 20 pts
Paper Review 20 pts
Daily HW 4 pts x 15 = 60 pts
Total 100 pts

The instructors may provide opportunities to earn additional points. Your final grade will be calculated from the final score as follows:
Score Grade
90 - 100 A
80 -  89 B
70 -  79 C
60 -  69 D
00 -  59 F




ASSIGNMENTS

Final Project
Overview:
You will plan, execute, and present a data analysis on a question of your own choosing. We encourage you to choose a question from your own research.
Due dates:
Analysis plan will be submitted as a HW - see schedule
Presentations will occur in class - see schedule
Presentation slides (if any) will be shared with the entire class (via slack)
Final reports due on the last day of class at 11:59PM
Name the report as follows: lastname-firstname-finalproject. For example, stewart-thomas-finalproject.pdf
Use a header so that each page prints your name in the top margin.
Instructions:
  • Choose a research question so that development of a predictive model makes sense.
  • Select a dataset that includes predictors of various types (both continuous and categorical).
  • Incorporate methods discussed in the course. (For example, transformations, splines, missing data methods, bootstrap, etc.)
  • Address model selection and fit.
  • Use graphical displays in both the report and the presentation.
  • Plan for a 15 minute presentation and 5 minutes of questions
  • Prepare a statistical analysis plan for your final project. The following is a suggested outline for the analysis plan.
    1. Introduction. This is a statistical analysis plan, so a (very) short introduction of the scientific / biological content is sufficient. Give the reader enough content to orient themselves.
    2. Context. List earlier studies that form the foundation of your current research project. As a statistical analysis plan, focus on the statistical aspects of the earlier studies, i.e., study design, patient population, analysis method, type of hypothesis test. Indicate how the project adds to or replicates earlier work.
    3. Research questions.
    4. Analysis plan. For each research question, provide information on the following:
      • Study design
      • Study population, inclusion/exclusion criteria
      • Variables
      • Statistical methods
      • Missing Data
      • Sensitivity analyses
      • Output. Provide mock-ups of tables and figures that summarize the results of the analyses. Mock-ups should be as complete as possible. Think how you might generate tables and figures that compare results from earlier research with the results from the present project.



Paper Review
Overview:
You will present to the class a critique of a published paper from a medical journal.
Due dates:
Discussion in class - see schedule

Presentation slides (if any) will be shared with the entire class (via zulip)
Use a header so that each page prints your name in the top margin.
Instructions:
  • Select a paper from the list of papers on zulip (or add a paper of your choice)
  • Review of the paper, focusing on the statistical analysis.
    • Identify strengths and weaknesses.
    • If there are issues with the analysis, explain what the issue is, how it may affect the analysis, and how you would analyze the data to avoid the issue.
  • Be prepared to discuss your critique and lead a discussion in class.
  • Read two other papers from the list of papers so that you may participate in the discussions during class



Daily Homework
Due:
The next class period after the question is assigned.
Include code if the problem requires STATA computation
Topic revision: r52 - 29 Jan 2021, ThomasStewart
 

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