Course Schedule
Sessions are held 10:00-11:00am US Eastern Time on most Fridays.
Links labeled “Offline discussion” for each section’s outline below will
take you to a dedicated datamethods.org topic for in-depth or
post-live session discussions. You can go directlly to the discussion
topic for session n by going to bit.ly/datamethods-bbrn
e.g. ...-bbr1
. Short questions and comments made during the
live broadcast should be entered in YouTube’s live chat. Here
is the link to the YouTube channel, and after each video premieres you
can go directly to the video for session by going to
bit.ly/yt-bbrn
.
NOTE: Beginning with Session 15 on 2020-04-03 and
lasting at least until the coronavirus crisis subsides, the course is
shifting to a “study at your own pace” mode with the scheduled 10am-11am
EDT time slot set aside for questions, answers, and discussions.
Discussions will take place on the datamethods.org
topic
listed for each session, supplemented by live video/audio/text chat on
Zoom. This mode
uses the course notes at hbiostat.org/bbr which will
automatically size to any viewing device. When studying the notes before
the online meeting, listen to audio narration and watch videos that are
linked from the notes in the right margin. For any questions or
discussion on datamethods
add any mnemonic shown in blue
boxes in the right margin of course notes (e.g. reg:ancova
)
somewhere in the datamethods
topic so that the course notes
will automatically link to that discussion. Contact Frank Harrell if you
would like to have a new mnemonic added to the course notes for linking
with a discussion you add in datamethods
.
Session 1: 2019-10-04
BBR Sections 3.1-3.7
- What is biostatistics?
- Statistical scientific method
- Types of data analysis
- Types of measurements
- Optimum response variables
- Offline
discussion
Moderators: Donald Szlosek (IDEXX Inc), Matt Shotwell
(Vanderbilt)
Session 2: 2019-10-11
BBR Sections 3.8-4.2
- Random variables
- Probability
- Distributions
- Descriptive statistics
- Watch in advance: 2-3 of the videos linked from the
camera icons in Section 3.9
- Offline
discussion
Moderators: Donald Szlosek (IDEXX Inc), Tom Stewart and Dandan Liu
(Vanderbilt)
Session 3: 2019-10-18
BBR Sections 4.3-4.4
Moderators: Donald Szlosek (IDEXX), Matt Shotwell and Tom Stewart
(Vanderbilt)
Session 4: 2019-11-01
BBR Sections 5.1-5.5
This session will be pre-recorded; for questions/discussion use only
the offline discussion link below.
- Statistical inference
- Hypothesis testing vs. asking questions
- Branches of statistics
- Errors in hypothesis testing
- Misinterpretations of p-values
- Interval estimation
- Offline
discussion
Session 5: 2019-11-15
BBR Sections 5.6-5.8
This session will likely be held live through a YouTube premier by
which a recorded video is played but the instructor engages in live chat
with participants. If this works the video will be viewed on the BBRcourse
YouTube Channel at 10am US Eastern Time.
- One sample test for means (Frequentist + Bayesian)
- One sample method for a probability (Frequentist + Bayesian)
- Paired data and one-sample tests
- Offline
discussion
Sesssion 6:
2019-12-06 BBR Sections 5.9-5.11
This session will be broadcast on the BBRcourse
YouTube Channel at 10am US Eastern Time Friday 2019-12-06.
- Two-sample test for means (Frequentist + Bayesian)
- How not to present results involving P-values
- Offline
discussion
Session 7:
2019-12-20 BBR Sections 5.12-5.14
- Study design considerations
- Sizing a pilot study using precision of SD
- Problems with standardized effect sizes
- Choice of effect size
- Multiple hypotheses and reasons not to multiplicity-adjust
- More about ordinal outcomes
- Study design big picture
- Crossover experiment example
- Offline discussion
Session 8: 2020-01-03
BBR Sections 6.1-6.9
- Comparing two proportions
- Normal approximation and Pearson \(\chi^2\) test
- Why not to use Fisher’s “exact” test
- Sample size
- Relative effect measures, especially odds ratio
Session 9: 2020-01-10
BBR Sections 6.10
- Introduction to logistic regression, for comparing proportions
- Bayesian logistic regression for comparing two proportions
Session 10:
2020-01-17 BBR Sections 7.1-7.5
- Nonparametric statistical tests
- When to use them
- One-sample Wilcoxon test
- Two-sample Wilcoxon test
- Confidence intervals for medians and differences in medians
Session 11:
2020-01-24 BBR Sections 7.6-7.8
- Generalization: proportional odds ordinal logistic model
- Power and sample size for Wilcoxon test and PO model
- Converting odds ratios in PO model to differences in
means/medians
- Advantages of PO model over Wilcoxon-Kruskal-Wallis tests
Session 12: 2020-01-31 BBR
Chapter 8
- Pearson and Spearman correlation coefficients
- Correlation vs. agreement; Bland-Altman plots
- Sample size calculation
- Why not to compare two correlations
- Avoiding overinterpretation when correlating many variables
February: Catch-Up Month
- Watch any of the 12 videos you haven’t seen yet
- Ask questions about material in session n at
http://bit.ly/datamethods-bbrn
Session 13:
2020-03-06 BBR Sections 10 - 10.5.8
- Stratification vs. matching vs. regression
- Purposes and advantages of statistical modeling
- Overview of nonparametric regression (smoothers)
- Simple linear regresion
Session 14: 2020-03-13
BBR 10.6-10.10.3
- Proper transformations vs. percentiling
- Multiple linear regression
- Two-sample t-test vs. linear regression
- Using regression for ANOVA
- ANCOVA
Session 15:
2020-04-03 BBR 9.4, 10.10.5-10.11.2
- Course notes: hbiostat.org/bbr
with audio narration and a few videos
- Zoom recording
- datamethods.org discussion
- Topics
- Analysis of continuous lead exposures with multiple linear
regression (Chapter 9 Sections 9.4-9.9)
- Two-way ANOVA (Chapter 10 Sections 10.10.5-)
- Interaction
- Internal vs. external validation
Session 16: 2020-04-24 BBR 14
- Course notes: Chapter 14 at hbiostat.org/bbr with audio
narration
- datamethods.org discussion
- Transformations
- Analysis of paired observations
- What’s wrong with change in general
- What’s wrong with percent change
- Objective method for choosing effect measure
- Example analysis
- Regression to the mean
Session 16 Web
Discussion: 2020-05-08 BBR 14
Session 17 Web Discussion
2020-05-22
- Video
- Open discussion about all topics covered so far in the course
Session 18: 2020-05-29 BBR 17
- Course notes
with audio narration
- datamethods.org discussion
- Topics
- Observational treatment comparison modeling strategy
- Problems and misunderstandings about propensity scores
- Role of interactions
Session 19: 2020-06-12 BBR 15
- Course notes with
audio narration
- datamethods.org discussion
- Topics
- Analysis of serial data
- Formal modeling approaches
- Summary statistic approach
- Case study
Session 20: 2020-06-27 BBR 21
- Course notes
- datamethods.org discussion
- Resources
- Topics
- Reproducible research
- Importance of sound methodology and adequate sample size on
reproducibility
- Pre-specification
- System forces working against reproducibility
- Literate programming and reproducible statistical reports
Session 21: 2020-09-04 BBR 22
- Course notes with
audio narration
- datamethods.org discussion
- Resources
- Topics
- What is a false positive
- Why is Type I assertion probability not an “error”
- What is Type I probability α?
- α vs. decision error probabilities
- Why α is not relevant to sequential Bayesian designs
Session 22:
2020-10-09 BBR 13 Section 13.1-13.5
- Course notes with
audio narration
- datamethods.org discussion
- Topics
- Analysis of covariance in randomized clinical trials
- Fundamental clinical question / estimand
- Why unadjusted risk differences, risk ratios, odds ratios, and
hazard ratios were intended only for homogeneous patients
- Difference between linear and nonlinear models
- Why are adjusted estimates right?
- How many covariables to use?
Session 23: 2020-10-16 BBR
13.6-13.10
- Course notes with
audio narration
- datamethods.org discussion
- Topics
- Analysis of covariance in randomized clinical trials
- Differential and absolute treatment effects
- Cost-effectiveness ratios
- Statistical plan for RCTs