Download ABS Summer School Multilevel Regression Analysis – Profs Heiner

ABS Summer School
Multilevel Regression Analysis – Profs Heiner Evanschitzky and Ad De Jong and Dr Yves Guillaume
15th – 17th July 2014
Pre-requisites/Target Audience:
The target audience for this course is early-career researchers and graduate students in Business and
Management, Psychology, and other social sciences, with an interest in latent variable and multi-level
modelling. Participants should be familiar with correlation and linear regression.
Overview:
This three-day workshop discusses general data analysis issues of cross-sectional studies. In
particular, it deals with multi-level (nested) data and offers hands-on software training. Key
objectives are:
a. To provide a solid refresher on multivariate statistics, particularly focusing on
topics important for multilevel analysis.
b. To familiarize participants with the key characteristics of nested data.
c. To enable participants to critically examine nested data with specific software and
draw meaningful conclusions.
d. To enable participants to apply (where suitable) multilevel analysis to their own
research.
e. To enable participants to conceptualize and test moderation and mediation in
multilevel models.
Experimental Design - Dr Julian Schmitt
21st-22nd July 2014
Pre-requisites/Target Audience:
The target audience for this course is early-career researchers and graduate students in
Business and Management, Psychology, and other social sciences, with an interest in designing
and conducting experiments. Participants should be familiar with basic statistics.
Overview:
The main objectives of this workshop are:
a. To familiarize participants with the key elements of experimental designs.
b. To enable participants to critically examine experimental settings encountered in research
papers.
c. To enable participants to build experiments for their own research.
Qualitative Comparative Analysis using Fuzzy Sets – Dr Matti Jaakkola
11th-12th August 2014
Pre-requisites/Target Audience:
The target audience for this course is early-career scholars in Business and Management, and other
social science disciplines, with an interest in set-theoretic methods. In addition to PhD students,
members of faculty may also find the topic useful in helping broadening their methodological tool
box. Participants are not expected to have prior knowledge of set-theoretic approaches. However,
they should find previous exposure to set theory and corresponding analytical approaches useful.
Overview:
1. Objectives
After completing this course, participants will:
(1) be familiar with set-theoretic approaches in social sciences
(2) understand the advantages and disadvantages of set-theoretic approaches in general,
and qualitative comparative analysis (QCA) in particular
(3) understand the analytical process of QCA
(4) be able to conduct different kinds of QCA with fs/QCA software, and report the findings
(5) be able to critically assess QCA-based research
The objectives will be achieved when participants actively engage with the lectures,
discussion of the supporting literature, and the data analysis sections of the course.
Introduction to Structural Equation Modelling with R – Dr Kristina Schmidt
13th-14th August 2014
Pre-requisites/Target Audience:
This course is useful for people from various backgrounds, particularly for (1) those seeking a
beginners’ to intermediate course in Structural Equation Modelling (SEM) and (2) those with
previous experience who wish to learn about using R, specifically the “lavaan” package. A basic
knowledge of introductory statistics (e.g., variance, covariance, correlation, and (multiple) regression
analysis) will be advantageous to participants; however, no prior knowledge or experience with SEM
or R is assumed. In general, this course may put more emphasis on basic or advanced topics in
accordance with the level of participants.
Overview:
The objective of this two day course is that at the end, participants will (1) have a good
understanding of the basic theory of SEM and (2) be able to implement SEM-type analyses with R.
Hence, this course will be taught as part lecture and part applied workshop.
Discriminant Validity Analysis - Dr Andrew Farrell
20th-21st August 2014
Pre-requisites/Target Audience:
The target audience for this course is early-career researchers and graduate students in Business and
Management, Psychology, and other social sciences, with an interest in latent variable modelling.
Participants should be familiar with exploratory and confirmatory factor analysis, and correlation and
linear regression.
Overview:
After completing this course, participants will:
(1) Be familiar with the theory of discriminant validity;
(2) Understand how to assess discriminant validity using a number of techniques;
(3) Understand the advantages and disadvantages of the various techniques;
(4) Be able to calculate and report discriminant validity assessment for latent variable models, using
popular software e.g. SPSS, LISREL, Lavaan/R
Process-based Studies in Qualitative Management Research – From Research Design to
Publication - Drs Stephanie Decker and Carola Wolf
27th-28th August 2014
Pre-requisites/Target Audience:
Basic understanding of qualitative research methodologies including basic research designs, data
collection strategies and analytical techniques. There are several introductory books on the market
that provide a good overview of these basics, for example
Flick, U. (2009). An Introduction to Qualitative Research. Sage: Thousand Oaks.
Miles, M. B., & Huberman, A. M. (1994). Qualitative Data Analysis. Sage: Thousand Oaks.
Overview:
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Data Mining and Big Data – Dr Ali Emrouznejad
1st-2nd September 2014
Pre-requisites/Target Audience:
Basic knowledge of calculus and statistics, quantitative skills would be an advantage
Overview:
The aim of this course is to introduce many of the important idea in data mining with focus of
analysing big data, explain them as statistical framework, and describe some of their applications in
Business, Finance, Marketing, and Management. Hence, this course covers data mining techniques
and their use in managerial business decision making.
Text Mining and Social Media – Dr Ali Emrouznejad
3rd September 2014
Pre-requisites/Target Audience:
Basic knowledge of calculus and statistics, quantitative skills would be an advantage
Overview:
The aim of this course is to introduce principles, issues, techniques and solutions connected with
text mining. At the end of this course students will gain knowledge of how recent advances in text
mining could help an organization to search for new knowledge by organising, characterising, finding
and exploiting large scale textual/unstructured information.
Meta-Analysis - Dr Yves Guillaume
15th-16th September 2014
Pre-requisites/Target Audience:
Participants should understand basic concepts of statistical inference. The concepts will, however,
be reviewed during the course.
Overview:
The course aims to provide participants with the understanding and experience to conduct a metaanalysis using the Hunter and Schmidt method. Specifically, participants will learn how to conduct a
meta-analysis of correlations (e.g., field studies) and effects sizes (e.g., intervention studies), correct
for common artifacts (e.g., sample size, measurement unreliability), and test for potential
moderators. Teaching will be example-based, drawing on real data to demonstrate the use of metaanalysis. Conceptual understanding will be emphasized without necessary technical detail.
Designing Cross-Country/Cross-National Research Studies – Dr Breno Nunes
8th September 2014
Pre-requisites/Target Audience:
Introductory level of knowledge on Business & Management studies (in particular international
business)
Recommended book: Charles W. L. Hill, International Business, 9th edition, McGraw-Hill Higher
Education, 2013
Introductory level of knowledge on Business & Management research methodologies (either
qualitative or quantitative):
Recommended books:
Lee, N., & Lings, I. (2008). Doing business research: a guide to theory and practice. Sage.
Creswell, J. W. (2013). Research design: Qualitative, quantitative, and mixed methods approaches.
Sage.
Overview:
Efficiency and Productivity Analysis using DEA
Emrouznejad
- Professor Emanuel Thanassoulis and Dr Ali
10th -11th September 2014
Pre-requisites/Target Audience:
Knowledge of linear programming will enable the participant to better understand the underlying
theory of DEA but it is not a pre-requisite. The DEA method will be applied using software which
automatically create and solve the models needed and so those unfamiliar with linear programming
will still be able to carry out assessments and interpret the findings.
Overview:
The aim of this course is to provide an understanding of performance measurement and management
using Data Envelopment Analysis (DEA). The focus is on applications both in the private and public
sector, enabling delegates to see how real situations can be modelled in the DEA framework to
estimate the scope for input and output improvements, including productivity change over time and
any scope for scale economies. The course would be of interest to those assessing performance of
organisational units, for instance, banks, hospitals, retail companies, energy companies, water
companies, hotels, schools, government departments.
The teaching is based on short interactive lectures with small group working on hands on examples
using appropriate software. The main objectives are to:
Learn about new methods in efficiency and productivity analysis;
Understand the principles behind DEA;
Get hands-on experience with the “PIM-DEA” software from the developers;
See how to improve the efficiency and productivity of decision making units;
Discussion of sample applications of DEA in the delegates’ workplace.
Mapping Decision Making: Causal Cognitive Mapping and Analysis - Dr Ian Combe
7-8 July 2014
Pre-requisites: None
Overview:
The course objectives are to:
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Develop an understanding of standardized cognitive research techniques used for mapping
decision making and their theoretical backgrounds
Develop an understanding of the types of research project that would benefit from cognitive
mapping techniques
Develop data collection skills use for eliciting cognitive maps
Develop the ability to use a cognitive mapping research software package
Develop an ability to conduct further analysis using Multidimensional scaling and Cluster
analysis