(Updated: September 01 2017 21:27)
Review of Regression
- Data craft, Fox (2016), ch. 1, 2, 3
- Linear models and least squares, Fox (2016), ch. 4 – 8
- Theory of linear models, Fox (2016), ch. 9
- Geometry of least squares, Fox (2016), ch. 10, Friendly et al. (2013)
- Diagnostics, Fox (2016), ch. 11 – 13
Review of Categorical Data
- Distributions and inference, Agresti (2007), ch. 1 – 2
- Contingency tables, Agresti (2007), ch. 2
Generalized Linear Models
- Logit and probit models for categorical response variables, Fox (2016) ch. 14
- Models for polytomous reponses, ch. 14.2
- Overview of contigency tables, ch. 14.3
- Structure of generalized linear models, Fox (2016) ch. 15.1
- Estimating and testing GLMs, Fox (2016) ch. 15.1.1
- GLMs for counts, Fox (2016) ch. 15.2
- Overdispersed count data, Fox (2016) ch. 15.2.1
- Theory of GLMs, Fox (2016) ch. 15.3
- Exponential families, Fox (2016) ch. 15.3.1; evans
- MLEs for GLMs, Fox (2016) ch. 15.3.2
- Hypothesis tests, Fox (2016) ch. 15.3.3
- Effect displays, Fox (2016) ch. 15.3.4
- Diagnostics for GLMs, Fox (2016) ch. 15.4
- Outlier, leverage and influence diagnostics, Fox (2016) ch. 15.4.1
- Nonlinearity diagnostics, Fox (2016) ch. 15.4.2
- Collinearity diagnostics, Fox (2016) ch. 15.4.3
- Complex sample surveys, Fox (2016) ch. 15.5
Loglinear Models
- Loglinear models for contingency tables, Fox (2016), ch. 15.2.2; Agresti (2007), ch, 7.
Special Models
- Models for matched pairs, Agresti (2007), ch. 8
Other topics
- Type permitting we will cover some other topics in Fox (2016) and Agresti (2007).
References
Fox, John. 2016. Applied Regression Analysis and Generalized Linear Models. 3rd ed. Sage Publications.
Friendly, Michael, Georges Monette, John Fox, and others. 2013. “Elliptical Insights: Understanding Statistical Methods Through Elliptical Geometry.” Statistical Science 28 (1). Institute of Mathematical Statistics: 1–39.