Schedule and location

Thursday December 8th – Friday December 9th  9:00-16:00

University of Jyväskylä, Jyväskylä, Agora building (visiting address: Mattilanniemi 2), room Lea Pulkkisen sali (4th floor, mornings) and computer class Ag B112.1 (afternoons).

Registration 

Registration is open until November 30th.

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 second course, we continue studying the use of regression analysis for research applications. We address how regression analysis can be used for estimating moderation and mediation models. Then we extend the regression model to nonlinear and non-normal case by introducing the generalized linear model and one of its variants, logistic regression. Calculating and plotting of marginal effects as way to interpret the regression results are covered. 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 first course.

Detailed Program

 Day 1 – Morning

Course introduction

Review of the first course content

Further issues in linear regression models

• Relationship between linear model and correlation matrix
• More on endogeneity
• Multicollinearity and other issues

Interaction (moderated and curved) effects

• Introduction to nonlinear effects
• Marginal effects and marginal plots
• Centering and collinearity
• Simple slopes tests

Discussion on the pre-class assignment (if time)

Day 1 – Afternoon (computer class)

Interaction (moderated and curved) effects

• Specification and estimation of nonlinear effects
• Marginal effects and marginal effects plots
• Effect size interpretation and reporting

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

Day 2 – Morning

Mediation effects

• Estimation of mediation models with regression
• Calculating and testing the direct effect
• Boostrap confidence intervals for the mediation effect

Generalized linear model (GLM)

• Introduction
• Maximum likelihood estimation
• Logistic regression
• More on link function and distribution family

Day 2 – Afternoon (computer class)

Excel exercise Maximum likelihood estimation

• Linear regression with maximul likelihood estimation
• Logistic regression

Mediation effects

• Estimation of mediation models with regression
• Calculating and testing the direct effect
• Boostrap confidence intervals for the mediation effect

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.