Schedule and location

Wednesday January 25th – Thursday January 26th  9:00-16:00

Registration 

Registration is open until January 18th.

Speakers

Dr. Mikko Rönkkö, University of Jyväskylä, Finland.

Organizer

Dr. Mikko Rönkkö, University of Jyväskylä, Finland.

Overview

Many researchers use quantitative research designs and statistical analysis tools without sufficient understanding on what these techniques are based on. This course is a part of a series of six courses where the goal is to develop an understanding of how multivariate statistical methods are used in information systems research and how results are usually presented in journal articles. The main goal of the course is to provide a foundation that enables independent self-study of quantitative research methods. Rather than addressing simply how the methods are used, we focus on why certain methods are used and how and why these methods work.

The course is designed for both those interested in just reading and understanding research done with statistical methods and for those who already use or plan to use statistical research methods in their own work.

During the course series we will go through six empirical papers published in leading IS and management journals, and analyze how these papers were done. The methods and research designs used in these papers cover a majority of methods and designs used in these journals. If you master all the methods and techniques presented during the course, you would be ideally capable to publish in these journals – if you have already a new theoretical insight and access to appropriate data.

In this third course, we address measurement. In many cases the concepts that we study cannot be directly observed, but can only be indirectly measured. The measurement process starts with concept definition, after which we develop one or more observable measures for assessing the concept. The two most important properties of measures are reliability and measurement validity. The course introduces these concepts as well as how factor analysis and other statistical techniques can be used to assess reliability and validity. In the computer class we will also go through basics of data management using statistical software. You can complete the course using either Stata, R, or SPSS.

The course has a pre-class readings package and a pre-class assignment that must be returned before the course and a post-class report that must be returned after the course. You should reserve at least two days for the pre-class assignment and at least a day for the post-class report. You can participate the course even if you did not participate on the  previous courses.

Detailed Program

 Day 1 – Morning

Course introduction

Measurement

• Conceptualization
• Reliability and validity in measurement
• Measurement theory

Classical test theory and cronbach's alpha

Introduction to factor analysis

• Dimensionality
• Discriminant and convergent validity

Discussion on the pre-class assignment (if time)

Day 1 – Afternoon (computer class)

Introducing the data-analysis assignment

Introduction to data management

• Reshaping
• Merging
• Working with longitudinal data

Day 2 – Morning

Exploratory factor analysis

Confirmatory factor analysis

Further issues in measurement

• Developing measurement items
• Item distribution and calibration
• "Formative measurement"

Discussion on the pre-class assignment (if time)

Day 2 – Afternoon (computer class)

Exploratory factor analysis and Cronbach's alpha

Confirmatory factor analysis

Working on the data-analysis assignment and post-class report

Credit points

Doctoral students participating in the seminar can obtain 2 credit points. This requires participating on both days and returning the pre-class assignment and post-class report.

Registration fee

This seminar is free-of-charge for Inforte.fi member organization's staff and their PhD students. For others the participation fee is 400 €. The participation fee includes access to the event and the event materials. Lunch and dinner are not included.