Bayesian Data Analysis
Monday
9:00 – 10:45
10:45 –
11:00
11:00 –
12:30
12:30 – 1:30
1:30 – 3:15
3:15 – 3:30
3:30 – 5:00
5:00 – 8:30
Tuesday
9:00 – 10:45
10:45 –
11:00
11:00 –
12:30
12:30 – 1:30
1:30 – 3:15
3:15 – 3:30
3:30 – 5:00
June 6, 2016
Bayesian reasoning generally
Snack and Refreshment Break
Perfidious pp values and the con game of confidence intervals
Lunch Break
Bayes’ rule, grid approximation, and R. Simple examples to train intuition.
Snack and Refreshment Break
Markov Chain Monte Carlo and JAGS. Complete programs for Bayesian
analysis.
Social hour and dinner for all Stats Camp attendees!
June 7, 2016
Hierarchical models. Shrinkage. Examples: therapeutic touch, baseball,
meta-analysis of extrasensory perception.
Snack and Refreshment Break
The generalized linear model. Simple linear regression; exponential
regression; sinusoidal regression, with autoregression component. Robust
versions of all.
Lunch Break
How to modify a program in JAGS & rjags for a different model. Multiple
linear regression. Logistic regression. Ordinal regression.
Snack and Refreshment Break
Hierarchical regression models: Estimating regression parameters at
multiple levels simultaneously.
Wednesday June 8, 2016
9:00 – 10:45 Hierarchical model for shrinkage of regression coefficients in multiple
regression.
10:45 –
Snack and Refreshment Break
11:00
11:00 –
Bayesian variable selection in multiple regression
12:30
12:30 – 1:30 Lunch Break
1:30 – 3:15
Model comparison as hierarchical model. The Bayes factor.
3:15 – 3:30
Snack and Refreshment Break
3:30 – 5:00
Two Bayesian ways to assess null values: Estimation vs model comparison.
Thursday
9:00 – 10:45
10:45 –
11:00
11:00 –
12:30
12:30 – 1:30
1:30 – 3:15
June 9, 2016
Bayesian hierarchical oneway “ANOVA”. Comparisons and shrinkage.
Snack and Refreshment Break
Models for unequal variances (“heteroscedasticity”).
Lunch Break
Bayesian hierarchical two way “ANOVA” with interaction. Interaction
contrasts.
3:15 – 3:30
3:30 – 5:00
Snack and Refreshment Break
Log-linear models and chi-square test.
Friday
9:00 – 10:45
10:45 –
11:00
11:00 –
12:30
12:30 – 1:30
1:30 - ~3:30
June 10, 2016
Power: Probability of achieving the goals of research.
Snack and Refreshment Break
The goal of achieving precision instead of rejecting/accepting a null value.
How to report a Bayesian analysis. Advanced topics as time permits.
Lunch Break
Individual Consulations