Detailed Programme
Detailed Programme
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Introduction to generalised linear models
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Data types.
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Review of linear regression model.
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Exponential family of distributions: introduction.
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Natural and scale parameters. Mean and variance. Variance function.
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Introduction to Generalized Linear Models: link functions, canonical link function, linear predictor.
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Variables, factors, interactions. Parametrisation.
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Deviance and scaled deviance.
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Pearson and deviance residuals.
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Statistical inference in the GLM
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Review of Maximum Likelihood theory.
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Point and interval estimation.
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Test of hypotheses on individual parameters.
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Test of linear restrictions - nested models.
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Model fit and model comparison.
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Estimation of dispersion parameter.
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Continuous response models
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The Normal model.
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The Exponential and Gamma models.
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Discrete response models
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The Binomial model.
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The Poisson model.
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Modelling of proportions.
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Poisson modelling of rates. Offest.
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Quasi-likelihood and overdispersion
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Introduction to quasi-likelihood estimation.
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Likelihood equations for the general and regression models.
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Choice of mean value and variance functions.
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Estimation of the dispersion parameter.
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