We are announcing two short courses, which are scheduled to take place in March and April 2009 at the University of Reading, UK. Summary information is given below. For more detailed information and registration forms please see http://www.reading.ac.uk/ssc providing your address and/or fax number, or email [log in to unmask]
Multilevel Modelling
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Dates: 30 - 31 March 2009. Duration: 2 days. Price: 665 GBP.
Hierarchical data structures are common in many areas of application, including the social sciences, education, market research, biology, psychology, agriculture and industry. Such data structures may arise from surveys, designed experiments or observational studies. The statistical analysis needs to correctly take into account the multilevel nature of these data; failure to do so could lead to incorrect conclusions.
Although the theory of multilevel modelling will be well explained, the emphasis in this course is on its practical implementation and interpretation of results. The course will focus on models with normally distributed errors.
The MLwiN package will be used in the presentations as well as other software as appropriate. In the practicals, in addition to MLwiN, participants will be able to choose from the statistics packages R, SAS, SPSS and Stata.
Multilevel Generalised Linear Models
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Date: 1 - 2 April 2009. Duration: 2 days. Price: 665 GBP.
This course extends the traditional multilevel model with normally distributed errors to those with discrete responses. Common discrete variables are binary and counts. Typically these types of responses are analysed using generalised linear models such as logistic regression and Poisson regression.
Commonly used generalised linear models will be extended to deal with multiple error structures, using a variety of examples. The emphasis will be practical, although an outline of the theory will be presented. Examples will be analysed using the specialised multilevel package MLwiN and other software such as SAS PROC NLMIXED or PROC GLIMMIX. In the practicals there will be a choice of R and Stata as well as SAS to complement the use of MLwiN.
Julia Harris
Short Course Administrator
Statistical Service Centre
Reading University
Tel: + 44 (0)118 378 8689
Fax: + 44 (0)118 378 8458
Email: [log in to unmask]
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