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Paul Gustafson
Course Outline (ps file) Assigned Coursework (ps file) R code used for examples Lecture 6 (Sept. 27): Simulation study for probit versus logit models Lecture 8(a) (Oct. 4): Deviance test for goodnessoffit in Poisson regression. Lecture 8(b) (Oct. 4): Likelihood ratio versus Wald test in Poisson regression setting. Lecture 9 (Oct. 6): Uncollapsed versus collapsed binary data. Lecture 10 (Oct. 13): Residuals with binomial data. Lecture 14 (Oct. 27): Understanding proportional odds and proportional hazards models. Lecture 15 (Oct. 27): Poisson versus multinomial modelling of count data. Lecture 18 (Nov. 15): Quasilikelihood (also rats data). Lecture 19 (Nov. 17): GLMM via penalized quasilikelihood. Lecture 20 (Nov. 22): GLMM via Bayes/MCMC. Lecture 21 (Nov. 24): Marginal models / GEE. Lecture 22 (Nov. 29): EM for missing data.


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