HALF-DAY WORKSHOPS:

• VECTORS, LOOPS AND OTHER DATA MANIPULATION TOOLS IN SPSS

• Introduction to R

14th OCTOBER 2010: York, UK

ASSESS is an independent user group for SPSS, a computer package for analysing and presenting data. It is run by users, for users and is completely independent of manufacturers of the software. Recent SPSS-related workshop topics by ASSESS have included syntax, macros, output management system (OMS) and Python.

Two half-day workshops are provisionally planned to be held in the Alcuin Research Resource Centre, University of York, on Thursday 14th October 2010. The workshops are suitable for SPSS users who are familiar with the menu toolbar but have limited knowledge of syntax. Workshop topics are at http://spssusers.co.uk/Events/2010/index.html. Both workshops will be taught in an interactive hands-on workshop-style format, with frequent examples and exercises for participants to work through. A full set of notes and example files will also be given to all who attend.

• Andrew Fenyo is the senior computing officer at the University of Kent in Canterbury, UK and has considerable experience providing SPSS support to staff and students. He is currently the treasurer of ASSESS.

• Professor MacKenzie  FIS, MSc, DIC, PhD, C.Stat, C. Sci., MFPHM (Hon.) is Director of the Centre of Biostatistics at the University of Limerick and currently visiting Professor of Statistics in ENSAI France. 

‘Vectors, Loops and other data manipulation tools in SPSS’ looks at passing on programming tips in SPSS to help get the most out of your data. Participants are welcome to bring along SPSS-related queries to this workshop relating to their own data which the tutor will be willing to answer.

‘Statistical modelling in R’ workshop picks up the R trail by reviewing general concepts of R and elements of last year's introductory R course.  Illustrations of the Linear Model function (LM) which was introduced in last year’s workshop and the Linear Mixed Effects function (LME) which was not will be given. LME allows us to fit a wide variety of Linear Mixed Models which are used for analysis of longitudinal data where the responses are repeated measures on the same subject or object. We also turn to generalisations of these models ie to GLMs, GLMMs, Survival and Frailty modelling. The course outline is available in word and pdf format

The ‘Vectors, Loops and other data manipulation tools in SPSS’ workshop lasts from 9-45am to 12-45pm and the ‘Statistical Modelling in R’ workshop from 2pm to 4-30pm. The booking fee includes a coffee break mid-workshop but not overnight accommodation.  A buffet lunch is also available

Booking Form

The booking form can be downloaded in Word format or in PDF format. Further details will be sent out to delegates upon receipt of booking forms. Delegates can choose to attend either or both workshops and/or the annual users meeting the following day.

An Introduction to R Course outline

Computer Training Room, Alcuin Research Resource Centre (ARRC), University of York, Thursday 14th October 2010; 2pm to 4pm.

This course builds on the Introductory Course presented in York last year. It is intended to instill confidence in statistical modelling in R.

We pick up the R trail by reviewing some general concepts of R and some elements of last year's course.  We illustrate these ideas via the use of the Linear Model function (LM)  which was introduced last year and the Linear Mixed  Effects function (LME) which was not.

LME allows us to fit a wide variety of Linear Mixed Models which are required, inter alia, for the analysis of longitudinal data where the responses are repeated measures on the same subject or object.  After coffee we turn to generalisations of these models ie to GLMs, GLMMs, Survival and Frailty modelling.

Throughout the course  participants will work through an annotated  R script  and have access to a pdf file with supporting theory. The examples will be main stream,  progressive and  will also illustrate the programming power of R in MLE based on the optimizer,  NLM. Additional data sets with examples from the literature will be supplied as required.

Programme Outline

1. Introduction Some general concepts and review.

2. Linear Models       Theory and examples

3 . Linear Mixed Models   Theory and examples.

Coffee 

4. GLMs    Theory and examples  

5. Generalized Linear Mixed Models  (GLMMs)       Theory and examples.

6. Survival & Frailty Models       Theory and examples

Further details at http://www.staff.ul.ie/mackenzieg; Follow the blue wedge to R Integration tools.