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MDSC 643.02 Biostatistics II

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Perpetual license is the best deal: US$134. You want Method 3 Grad Plan' Then: Vicki Stagg will contact you. vlstagg_at_ucalgary.ca. 220-7265. Appointments to see GHF ... – PowerPoint PPT presentation

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Title: MDSC 643.02 Biostatistics II


1
MDSC 643.02Biostatistics II
  • Gordon Hilton Fick
  • ghfick_at_ucalgary.ca
  • www.ucalgary.ca/ghfick
  • 220-6939

2
Teaching Assistants
  • Jian Kang
  • Office hours and some large group sessions
  • Shelly Vik
  • Marking and grading

3
Stata
  • First
  • Phone Stata Corporation 800-248-8272
  • Intercooled Stata 8 is recommended
  • Perpetual license is the best deal US134
  • You want Method 3 Grad Plan
  • Then
  • Vicki Stagg will contact you
  • vlstagg_at_ucalgary.ca
  • 220-7265

4
Appointments to see GHF
  • Crystal Elliott
  • elliottc_at_ucalgary.ca
  • 220-4288
  • Monday afternoons are best
  • Other days and/or times are possible too

5
Assignments
  • Interpretation most important
  • All Stata analyses must be explained
  • Define all terms in context
  • Use Equations editor to make symbols

6
Prerequisite Course
  • MDSC 643.01 Biostatistics I
  • B or better
  • Within the past 3 years
  • See GHF if you have other preparation

7
Prerequisite material
  • Interpret accurately and completely
  • boxplots, scatterplots, line plots, axes, units,
    titles
  • mean versus median when?
  • data transformations
  • tests and confidence intervals
  • tables FET versus tests
  • means t-tests, analysis of variance
  • matched analysis

8
Computing Background
  • Windows/Mac/Linux architecture
  • Website links, left versus right clicks
  • Stata Rabe-Hesketh Everitt
  • Chapters 1 2

9
Projects
  • Grouped In pairs
  • Power Point presentations
  • To display biostatistical content
  • 10 minutes for each group

10
Course Objectives
  • Health Studies From idea, to design, to data
    collection, data analysis and interpretation
  • Linking classical analyses to model-based
    analyses
  • Using software spreadsheet/database to
    statistical analysis
  • Linear regression and Logistic regression
    choosing, assessing, interpreting
  • Introducing other regression models conditional
    logistic, proportional hazards and others
  • Using models to assess potential confounders
    and/or modifiers
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