GRADES

Your grade in this class is calculated from your scores on (a) 5 assignments and (b) in-class activities. The 5 assignments are each worth 16 points (80 points in total). All combined, the in-class activities are worth 20 points. Your final score in this course will be the sum of the points earned on the assignments and in-class activities. 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 part of HW 3 on 22 Februrary 2016
Presentations in class on 26 & 29 February 2016
Final reports due by 29 February 2016 at 11:59PM
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



Paper Review
Overview:
You will present to the class a critique of a published paper from a medical journal.
Due dates:
Discussion in class on 18 February 2016
Written review of paper will be collected after in class discussion
Instructions:



Homework 1
Due dates:
Due 6:00AM on 8 February 2016
Email a single document to the TA
Include code
Problems:
  1. Read the description of the data in ABD chapter 17 problem 1. The dataset is available from ABD Datasets as 17-q-01.
    1. Plot the data in a scatter plot. Plot the estimated linear regression line with the scatter plot.
    2. Report the parameter estimates and confidence intervals of the regression line as one might find them in a medical journal.
    3. Write the parameter estimates of the regression line in the form of an equation.
    4. Interpret each parameter in the model.
    5. What do the confidence intervals communicate?
    6. Create a scatter plot with the regression estimate and confidence band.
  2. Do ABD chapter 17 problem 3. Instead of calculating values by hand, use STATA.
  3. Do ABD chapter 17 problem 8.a
  4. Do ABD chapter 17 problem 16
  5. Do ABD chapter 17 problem 20. Data available in ABD Datasets.
  6. Do ABD chapter 17 problem 21. Data available in ABD Datasets.
  7. Do ABD chapter 17 problem 28. Data available in ABD Datasets.
  8. Do ABD chapter 18 problem 10
  9. Do ABD chapter 18 problem 11. Data available in ABD Datasets.
  10. Do ABD chapter 18 problem 12. Data available in ABD Datasets. Reproduce the figure in the question.
  11. Do ABD chapter 18 problem 15. Data available in ABD Datasets. Reproduce the figure in the question.
  12. Do ABD chapter 18 problem 18. Data available in ABD Datasets.
  13. Please provide feedback:
    1. Which problems in this assignment did you feel least prepared to answer, if any?
    2. How much time (in hours) did you spend completing this assignment?
    3. Where there topics covered in readings or lecture that you expected to see included in this assignment, but were not? If so, which?
    4. Any other comments?



Homework 2
Due dates:
Due 6:00AM on 15 February 2016
Email a single document to the TA
Include code
Problems:
  1. Do RMS chapter 2 problem 1.
  2. Do RMS chapter 2 problem 2.
  3. Do RMS chapter 2 problem 3.
  4. Do RMS chapter 2 problem 4.
  5. Do RMS chapter 2 problem 5. Data available at http://biostat.mc.vanderbilt.edu/MsciBiostatIIAssignments/sat.csv.
  6. Please provide feedback:
    1. Which problems in this assignment did you feel least prepared to answer, if any?
    2. How much time (in hours) did you spend completing this assignment?
    3. Where there topics covered in readings or lecture that you expected to see included in this assignment, but were not? If so, which?
    4. Any other comments?



Homework 3
Due dates:
Due 6:00AM on 22 February 2016
Email a single document to the TA
Include code
Problems:
  • With the original data from ABD chapter 19 problem 11 (First 18 obs of 19-q-11):
    1. Fit a simple linear model with spermstored as outcome and shellvolume as predictor.
    2. Plot the data and the regression model.
    3. Calculate the correlation coefficient.
    4. Use bootstrapping to generate a confidence interval for the correlation coefficient.
    5. Explain the advantages of the bootstrap confidence interval in this situation?
  • With thedata from ABD chapter 19 problem 13 (19-q-13):
    1. Provide a bootstrap estimate of the 95% confidence interval of the median.
    2. Provide a bootstrap estimate of the 95% confidence interval of the 75th percentile.
  • 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.
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