Statistical Collaboration Health Sciences II

Instructors MarioDavidson
Course Number 2014.01.SPR.GS.BIOS.352
Meeting Times Monday 1:00pm - 3:00pm
Course Location 2525 W. End Ave; 11139
Office Hours by request

Course Description

  • Goal: To develop the knowledge, skills, attitude, and behavior necessary to interact with research collaborators and statistical clients.
  • Each course session will take one of two alternating types. The first type will concern real world consulting or expert input on specialized statistical topics. The second type of session will pursue real consulting problems, including their technical aspects.
  • Expectations: Students are expected to participate in classroom discussions, projects, and presentations. Because participation is a portion of the grade, students are expected to attend all sessions. The instructors should be informed beforehand if a student is unable to attend class.
  • All forms of verbal, physical, and written communication are expected to be professional. Students are strongly encouraged to dress professionally for all of Dr. Davidson's sessions.

Course Material and Resources

Students should bring a laptop to class, and are encouraged to follow along with computer demonstrations. Personal laptops with a statistical software should be brought to every class. Participants are expected to have access to MS Excel and Word (or an equivalent such as Open Office). Microsoft Office products are available at the Vanderbilt Software Store. A typesetting language is not mandated but encouraged. Data sets may be found in the "External Links" in OAK, on this wiki page, or a sub-page. Writing resources may be found at the Vanderbilt Writing Studio. The studio is free for Vanderbilt University students.
  • Text: Statistical Consulting: A Guide to Effective Communication, Janice Derr, ISBN-10: 0534362281, ISBN-13: 978-0534362287

Honor Code

Vanderbilt's Honor Code governs all work in this course. Students may discuss the assignments outside of class, but each student's writing and presentation of the data is expected to be original and independently finalized unless stated otherwise by the instructor. Direct quotes need to cite the source in quotes; otherwise, it is consider plagiarism. If you have any questions about the application of the honor code to this course, please do not hesitate to ask the instructors.

Assignments and Assessment

Assessments and feedback may be found in OAK. Assignment should be dropped into the "Assignment" folder in OAK under the appropriate due date and topic. All dropped assignments should be an attachment. Late assignments will be penalized as such: the first day 20%, the second day 40%, and the third day 100%. Assignments may be turned in earlier than the due date. Videos of the consultations may be found at Consulting Videos.
  • (45%) Written Statistical Communication Assignments
  • (45%) Statistical Assignments
  • (10%) Biostatistics Clinic Attendance
Numerical scores will be rounded to the nearest tenth. Letter grades will be assigned as defined by the following ranges:
Letter Grade Lower Score Upper Score
A+ 96.5 100.0
A 93.5 96.4
A- 90.0 93.4
B+ 86.5 89.9
B 83.5 86.4
B- 80.0 83.4
C+ 76.5 79.9
C 73.5 76.4
C- 70.0 73.4
D+ 66.5 69.9
D 63.5 66.4
D- 60.0 63.4
F 0.0 59.9

Schedule

Assignment of Roles for Consultations

Description of Roles

Biostatistician trainees are required to complete multiple projects. A description of the possible roles are below.

Leader
  • Responsible for:
    • managing the project until completion by the deadline(i.e. If a team member is not pulling their weight, the leader is responsible for making sure their part is accomplished.)
    • understanding the topic
    • critically assessing the consultation

Scribe
  • Responsible for:
    • writing the meeting minutes
    • creating a realistic data set and dictionary
    • contacting the investigator (only when necessary on a LIMITED basis)
SAP Writer
  • Responsible for:
    • writing the analysis plan
Analyst
  • Responsible for:
    • cleaning the data
    • analyzing the data,
    • creating graphs
    • creating tables
Final Report Writer
  • Responsible for
    • creating a final report

Meeting Date Investigator Leader, Background, and Consulting Reflection Scribe, Data Dictionary, and Data SAP Writer Analyst Final Report Writer Deadline
02/03/14 Charlene Dewey DS CT MZ MG AL 02/17/14
02/17/14 Amy Fleming CT MZ MG AL DS 03/10/14
03/10/14 Regina Russell MZ MG AL DS CT 03/24/14
03/24/14 Tyler Reimschisel MG AL DS CT MZ (First draft) 04/07/14
04/07/14 Oscar Guillamondegui will visit but Dr. Reimschisel's project will be due. No project will be due for Guillamondegui AL DS CT MZ MG 04/21/14

2014/01/06 (MD)

  • Ayumi Shintani: Working with, Supervising, and Developing a Team of Biostatisticians
  • Rafe Donahue: Comparing Academic and Industry Biostatisticians

2014/01/13 (MS)

  • Select/propose technical topics for future class discussion:
    • Evaluating model building/selection algorithms
    • Combining mathematical and statistical models
    • Web-based reporting (reproducible research) frameworks
    • Double bootstrap ideas
  • Four model selection strategies:
    • "Stepwise"
    • "Bottom Up"
    • "Bottom Step"
    • "Full Model"
  • Link to the figures: https://data.vanderbilt.edu/collab/shotwems/ModelSelection/
  • Code used to draw figures: selection.R
  • Assignment:
    • Evaluate the "full model" and one other model selection method in an alternative scenario, where the data, modeling approach, and inferential goals are different. You may use the code provided ( selection.R) as a starting point. Your evaluation need not focus on the distributions of model coefficient estimators, but should be relevant to the scenario. Prepare a reproducible report of your findings.

2014/01/20 (MLK Day; No Class)

2014/01/27 (MS)

  • last class: S.E. of X1 coefficient depends on selected model
  • last class: selected model depends on sample

DirectedGraphPlugin_1.png diagram

2014/02/03 (MD)

  • William Dupont: Grant Writing as a Collaborator or Primary Investigator.
  • Consultation with Charlene Dewey

2014/02/10 (MS)

2014/02/17 (MD)

  • Consultation with Amy Fleming
  • Elizabeth Heitman: Ethics

2014/02/24 (MS)

dat <- read.csv(paste0("http://biostat.mc.vanderbilt.edu/",
                       "wiki/pub/Main/CourseBios352/",
                       "example-data.csv"))

2014/03/03 (Spring Break; No Class)

2014/03/10 (MD)

  • Consultation with Regina Russell
  • Stephen Jones: Health Industry Recruiter
  • Rafe Donahue: Comparing Academic and Industry Statisticians (Makeup day: 3-4)

2014/03/17 (MD)

  • Teaching Statistics, Discussion about Projects, and/or Student Meeting Time about Projects (TBD)
  • Tatsuki Koyama: Working with, Supervising, and Developing a Team of Biostatisticians (Make-up Day)

2014/03/24 (MD)

  • Consultation with Tyler Reimschisel
  • Questionnaire Design

2014/03/31 (MS)

2014/04/07 (MD)

  • Creating Effective and Visually Attractive Scientific Posters: Making People Stop!
  • Consultation with Oscar Guillamondegui

2014/04/14 (MS)

2014/04/21 (MD)

  • Consultation with Leora Horn
  • Brian Griffith: Developing Your Personal Plan

2014/04/28 (Finals Week)

  • No Class

Topic attachments
I Attachment Action Size Date Who Comment
BIOS352FinalProject.pdfpdf BIOS352FinalProject.pdf manage 79.7 K 19 Apr 2013 - 10:54 MattShotwell  
Biexp.RnwRnw Biexp.Rnw manage 6.8 K 31 Mar 2014 - 11:32 MattShotwell Collaborative Grant Writing Template
Biexp.pdfpdf Biexp.pdf manage 90.2 K 31 Mar 2014 - 11:32 MattShotwell Collaborative Grant Writing Assignment
Example.pdfpdf Example.pdf manage 88.6 K 31 Mar 2014 - 11:33 MattShotwell Collaborative Grant Writing Example
asymptotic-standard-error-comparision.pngpng asymptotic-standard-error-comparision.png manage 8.2 K 27 Jan 2014 - 10:57 MattShotwell  
bootstrap-standard-error-comparison.pngpng bootstrap-standard-error-comparison.png manage 8.2 K 27 Jan 2014 - 10:58 MattShotwell  
example-data.csvcsv example-data.csv manage 0.3 K 24 Feb 2014 - 12:31 MattShotwell example data
full-asymptotic-standard-error-comparison.pngpng full-asymptotic-standard-error-comparison.png manage 8.4 K 27 Jan 2014 - 11:58 MattShotwell  
full-bootstrap-standard-error-comparison.pngpng full-bootstrap-standard-error-comparison.png manage 8.0 K 27 Jan 2014 - 11:58 MattShotwell  
mean-absolute-error-comparison.pngpng mean-absolute-error-comparison.png manage 39.9 K 27 Jan 2014 - 10:58 MattShotwell  
selection.RR selection.R manage 14.0 K 13 Jan 2014 - 12:45 MattShotwell Code for simulating model selection strategies
simpsons-paradox.pngpng simpsons-paradox.png manage 24.4 K 27 Jan 2014 - 11:07 MattShotwell  
stepwise.RR stepwise.R manage 4.8 K 15 Jan 2013 - 10:38 MattShotwell Stepwise versus "Full Model" comparison script
Topic revision: r62 - 28 Sep 2014, MattShotwell
 

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