Example analyses with JAGS and R
6
GLM for binomial data
Bayesian Inference for Biologists
Welcome
Introduction to Bayesian inference
1
Introduction: Modes of inference
2
Probability and Bayes’ theorem
3
Introduction to JAGS and MCMC
Example analyses with JAGS and R
4
Linear models, Bayesian style
5
GLM for count data
6
GLM for binomial data
7
GLM for continuous data
8
Nonlinear models in JAGS
9
Mixed models and random effects
Special applications of Bayesian inference
10
Mark-recapture analysis
11
State space models
References
Table of contents
6.1
Logistic GLM for binary outcomes
6.1.1
Definition
6.1.2
Example
6.2
Binomial GLM for proportions
6.2.1
Definition
6.2.2
Example
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Example analyses with JAGS and R
6
GLM for binomial data
6
GLM for binomial data
6.1
Logistic GLM for binary outcomes
6.1.1
Definition
6.1.2
Example
6.1.2.1
Data generation
6.1.2.2
Frequentist analysis
6.1.2.3
Bayesian analysis
6.2
Binomial GLM for proportions
6.2.1
Definition
6.2.2
Example
6.2.2.1
Data generation
6.2.2.2
Frequentist analysis
6.2.2.3
Bayesian analysis
5
GLM for count data
7
GLM for continuous data