Explains measurement error and misclassification, including how biased proxies can distort effects and how causal graphs and Bayesian models account for uncertain measurements.
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Statistical Rethinking (2023)
All
- 01-Science Before Statistics
01-Science Before Statistics
- 02-Garden of Forking Data
- 03-Geocentric Models
- 04-Categories and Curves
- 05-Elemental Confounds
- 06-Good and Bad Controls
- 07-Overfitting
- 09-Modeling Events
- 10-Counts and Confounds
- 11-Ordered Categories
- 12-Multilevel Models
- 13-Multilevel Adventures
- 14-Correlated Features
- 15-Social Networks
- 16-Gaussian Processes
- 17-Measurement
- 18-Missing Data
- 19-Generalized Linear Madness
- 20-Horoscopes