Psi Training Course

A Two Day Course on Discrete Data Modelling

Presented by

Professor Alan Agresti

6th & 7th October 2016 Venue: The Royal Statistical Society, 12 Errol Street, London, EC1Y 8LX Nearest Tubes: Barbican, Liverpool Street, Moorgate, Old Street

This course provides an applied overview of statistical methods for analysing discrete data, from the Course perspective of generalized linear modelling. Each method is illustrated with an example, mainly using R Summary: software but also often showing SAS and Stata code and output. Topics include models for binary response data, multicategory data, count data, overdispersed and zero-inflated data, and correlated and clustered discrete response variables.

The main objective of the course is to introduce attendees to the most important statistical methods for analysing discrete data. Special emphasis will be placed on categorical data, which are very common in practice, and when there are more than two categories, different methods apply for ordered than for Learning unordered categories. It is useful for a methodologist to know the various options for analysing such Outcomes: data as well as the pros and cons of those approaches. The main focus will be on introducing various models and their interpretations, and showing how to implement them. Through examples, the attendees will learn how to use the models and will understand the advantages and disadvantages of the various model types. Although software emphasis will be on R, many of the examples will also show SAS and/or Stata code and output.

Topics Topics include logistic regression and probit models for binary data, baseline-category logit and cumulative logit models for multicategory data, Poisson and negative binomial regression models for Covered: count data, zero-inflated models, overdispersion methods including quasi-likelihood and beta-binomial models, and marginal models and random effects models for correlated categorical response variables.

Target People with a background in applied statistics, including basic regression and ANOVA. A typical Audience: attendee might be a statistician or biostatistician working in government or industry who never had an academic course covering the topics treated in this short course. Knowledge Basic statistical modelling, such as regression and ANOVA, and confidence interval and significance test Assumed: methods used in them that are based on the likelihood function (such as maximum likelihood estimation and likelihood-ratio tests).

Course Lecture with worked examples using R software, with many examples also having SAS and/or Stata code and output, plus two hours for practicals. Begin about 9 am and end about 5:30, but attendees who Format: do not want to participate in practical sessions can leave earlier.

Fees Registration before Registration on / after (incl VAT) 7 September 2016 7 September 2016

Non Member £562.50+vat £625+vat

RSS Fellow £478.12+vat £531.25+vat

RSS CStat: also MIS, FIS & GradStat £450+vat £500+vat

Tessa Pearson, Royal Statistical Society, 12 Errol Street, London EC1Y 8LX. Contact: Tel: +44 (0)20 7614 3947 Email: [email protected] Fax: +44 (0)20 7614 3905

Non-members are welcome to join the Society at the same time as registering for the course and the discount received will cover the cost of their first subscription payment. More information about membership can be found at www.rss.org.uk/join REGISTRATION FORM Discrete Data Modelling – 6 & 7 October 2016

PLEASE USE ONE FORM PER PERSON. Completed forms may be faxed to + 44 (0)20 7614 3905

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Non-member (£562.50+vat) £675.00 □ Non-member (£625+vat) £750.00 □

RSS Fellow (£478.12+vat) £573.75 RSS Fellow (£531.25+vat) £637.50 □ □ CStat, MIS, FIS and GradStat (£500+vat) £600.00 □ CStat, MIS, FIS and GradStat (£450+vat) £540.00 □

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Please return Tessa Pearson, Royal Statistical Society, 12 Errol Street, London EC1Y 8LX. completed form to: Tel: +44 (0)20 7614 3947 Email: [email protected] Fax: +44 (0)20 7614 3905