Apologies for cross-posting. We would like to announce two workshops on statistical modelling in January 2016:
1) Introduction to Statistical Modelling (12th - 15th Jan 2016) and 2) Flexible Models for Correlated Count or Multi-Category data (18th - 21st Jan 2016) The Centre for Research into Ecological and Environmental Modelling (CREEM) at the University of St. Andrews will be running two 'Statistical Modelling' workshops to introduce both basic and more advanced techniques. Introduction to Statistical Modelling (4 days) This workshop will take place 12th - 15th January 2016 and will cover Exploratory Data Analysis, Confidence Intervals, Linear Models, Generalised Linear Models to help participants analyse continuous, presence/absence and count data and Generalised Estimating Equations for modelling correlated data. Flexible Models for Correlated Count or Multi-Category data (4 days) This workshop will take place 18th - 21st January 2016 and covers one dimensional and two dimensional smoothing using more traditional and recently developed methods. The correlated aspect of the data is addressed using Generalised Estimating Equations (GEEs). These will be covered in more detail than in the introductory workshop. The initial example will be using count data (Poisson) however towards the end of the workshop we will also cover models for categorical data (e.g. Binomial, Binary and Multinomial response types). Both courses will be heavily data-based and presented using large scale offshore wind farm and clinical trials data. The R software package will be used for workshop-based practicals. Computer sessions take place in our computer classroom (attached to the seminar room) and participants can use our computers or bring their own laptops. For more information and registration, please visit the webpage: http://creem2.st-andrews.ac.uk/introduction-to-statistical-modelling-and-spatial-modelling-methods-for-correlated-data-workshops-2/ Please note that early registration closes on the 14th December. Many Thanks, Lindesay Scott-Hayward
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