Advanced Quantitative Methods Summer School 2018

The Quantitative Methods Hub at the Department of Education, University of Oxford, offers its annual Advanced Quantitative Methods Summer School, this year consisting of seven different course days in week 3 and 4 of Trinity Term (8 – 17 May 2018). The courses require an understanding of multiple regression modelling or other multivariate techniques.

All courses will take place in the Department of Education, 15 Norham Gardens, Oxford, OX2 9AZ (Seminar Room D or E)

Students and staff are welcome to attend one, some or all days.
Courses will cost £25 for OU and Grand Union students, £100 for staff and external students, or £320 for the week. Lunch and refreshments included in price.

Please note that participants are required to bring their own laptops.

Number of spaces available per course: 25

Week 1 Programme

Introduction to Item Response Theory (IRT) Models 

Tuesday 8 May
Instructor: Joshua McGrane
Time: 10.00 – 15.30
Course prerequisites: It is assumed that participants will have a background in basic statistical methods and familiarity with statistical software.
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Introduction to R

Wednesday 9 May
Instructor: Thees F Speckelsen
Time: 10.00 – 16.30
Course prerequisites: It is assumed that participants will have a background in basic statistical methods up to, and including, regression analysis. Familiarity with syntax language from other statistical packages (eg. Stata, SPSS) is desirable.
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Multilevel models for educational data

Thursday 10 May Multilevel models for educational data
Instructor: Daniel Caro
Time: 10.00 – 15.30
Course prerequisites: Participants need to understand the basics of multiple regression, or other relevant multivariate statistics. 
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Introduction to structural equation models (SEM)

Friday 11 May 
Instructor: Lars Malmberg
Time: 10.00 – 15.30
Course prerequisites: Participants need to understand the basics of multiple regression, or other relevant multivariate statistics
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Week 2 Programme

Simulation in theory and practice

Tuesday 15 May
Instructor: Prathiba Natesan
Time: 10.00 – 15.30
Course prerequisites: Participants will need to know basics of univariate statistics and general linear models. Working knowledge of R is preferred although not required. The course will have a brief introduction to R.
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Longitudinal SEM

Wednesday 16 May
Instructor: Lars Malmberg
Time: 10.00 – 15.30
Pre-requirements: Participants need to understand the basics of multiple regression, other relevant multivariate statistics, and have some exposure to either multilevel regression or SEM.
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Multilevel SEM

Thursday 17 May
Instructor: Lars Malmberg
Time: 10.00 – 15.30
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