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Quantitative Measurement and Analysis (Spring 2022) - ONLINE - 6 ECTS
Date and time
Wednesday 23 March 2022 at 09:00 to Thursday 21 April 2022 at 16:00
Registration Deadline
Wednesday 23 March 2022 at 09:00
Location
Room TBA,
Campus TBA,
2000 Frederiksberg
Room TBA
Campus TBA
2000 Frederiksberg
Quantitative Measurement and Analysis (Spring 2022) - ONLINE - 6 ECTS
Event Description
| Faculty | ||
| Chee-Wee Tan, Michel Avital, and additional faculty members as needed. | ||
Course Coordinator |
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| Professor Chee-Wee Tan & Professor Michel Avital | ||
Prerequisites |
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| Prerequisite Statistical Software Tools: Although the course is designed to be software agnostic, we will deal primarily with SPSS, SmartPLS, and STATA because they are available for download from CBS or for free. Prior to the first class, please obtain, install, and get familiar (using the online tutorials) with the basic operation of the two required statistical software application: SPSS, SmartPLS, and STATA. Required: ▪ IBM SPSS [Downloadable from http://my.cbs.dk] ▪ SmartPLS [SmartPLS 3 purchasable from http://www.smartpls.de, but for this course, you can obtain a free copy of SmartPLS 2.0.M3 by entering your contact information in the fields located at the bottom of this URL: https://www.smartpls.com/smartpls2] ▪ STATA [Downloadable from http://my.cbs.dk] Optional: ▪ LISREL [Purchasable from http://www.ssicentral.com/lisrel/index.html, but for this course, a free student copy can be downloaded via http://www.ssicentral.com/lisrel/student.html] ▪ fs/QCA [Downloadable from http://www.u.arizona.edu/~cragin/fsQCA/software.shtml] |
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Aim |
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| The Quantitative Measurement and Analysis course is designed for doctoral students who are interested in pursuing quantitative research projects in social sciences. A primary objective of the course is to help participants acquire the necessary skills that will enable them to design, execute, report and critically review quantitative research in social sciences with an emphasis on management and administrative social science fields.
Participants will gain foundational knowledge of quantitative research methods and the considerations that go into the design of empirical studies employing such methods. |
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Course content |
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| The course is designed as a bi-weekly sequence of three 2-day blocks, each covering a key topic on quantitative research methods in social sciences. The meetings are in the form of participatory seminars that comprise class presentations, directed discussions and practical workshops. In addition to an appreciative and/or critical review of extant literature on quantitative research methods, the seminars seek to encourage constructive dialogue aimed at helping students to tackle research questions in a quantitative fashion, which builds on and extends contemporary knowledge. Meetings are held on a bi-weekly basis to allow sufficient time for in-depth reading and reflection.
Given the aforementioned learning objectives, the course is designed with a heavy reading load. Reading the materials beforehand and participating actively in class assignments and dialogues are essential for getting a firm grasp of the course content. For each block, students should read the assigned articles and be prepared to answer questions and discuss any other issues pertaining to the assigned reading material. Furthermore, students will be expected to prepare a take-home assignment that will be discussed in the next class. Research Proposal Presentation [last class] For the last session of the course, each student will be expected to prepare a presentation that outlines the design of a quantitative empirical study for investigating their domain of interest or any other contemporary or emerging topic in social sciences. The purpose of the presentation is to familiarize students with the practical steps involved in conducting quantitative empirical studies. The presentation should incorporate the following elements: ▪ Selected topic to be investigated via quantitative research models ▪ Significance of the selected topic ▪ Prior research on the selected topic ▪ Research question(s) to be answered based on the selected topic ▪ Theoretical model and hypotheses for answering the research question(s) ▪ Quantitative research strategy being adopted to validate the theoretical model and hypotheses ➢ Instruments for data collection ➢ Possible data source(s) ➢ Proposed data analytical technique(s) to be utilized ▪ Potential contributions to theory and practice |
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Teaching style |
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| The course will run online using Zoom. Participants need to ensure that they are on a high-speed internet connection. They also commit to 100%s presence with face camera on and active participation in discussions during course days.
Evaluation: Individual take-home 15 pages written exam together with a research proposal presentation will form the basis for evaluating students’ performance. The written exam and the presentation will have equal weight in the course grade. Grading is based on the standard 7-step scale. A passing grade on two individual 5 pages written homework assignments is a prerequisite for taking the exam. Homework Assignments: Two mandatory individual 5 pages written homework assignments are designed to reinforce key analytical technics and provide an opportunity for deeper learning and reflection. The assignments cover exploratory factor analysis and structural equation modeling. |
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Lecture plan |
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| Block 1 Week 12
Wednesday - Mar 23, 2022 D1P1 09:00-12:00 Building Blocks in Context: Theory and Theorizing, Modeling, Relationships and Hypotheses, Constructs and Variables D1P2 13:00-16:00 Measurement: Measurement Properties, Construct Validity, Scale Development and Exploratory Factor Analysis (EFA) Thursday - Mar 24, 2022 D2P1 09:00-12:00 Primary Data Collection: Survey Research and Sampling D2P2 13:00-16:00 Experimental and Quasi-Experimental Research Block 2 Week 14 Tuesday -Apr 5, 2022 D3P1 09:00-12:00 Recap Measurement (and go over exercise) Ex 1 EFA (Deadline: March 31st, 2022) D3P2 13:00-16:00 Structural Equation Modeling (SEM): Confirmatory Factor Analysis (CFA), LISREL, Regression and Partial Least Squares (PLS) Wednesday - Apr 6, 2022 D4P1 09:00-12:00 Structural Equation Modeling (SEM): Model Specification, Second-Order Constructs and Common Method Bias (CMB) D4P2 13:00-16:00 Mediation and Moderation Block 3 Week 16 Wednesday - Apr 20, 2022 D5P1 09:00-12:00 Recap SEM (and go over exercise) Ex 2 SEM (Deadline: April 15th, 2022) D5P2 -13:00-16:00 Secondary Data Sets: Secondary Data Analysis, Meta-Analysis and Qualitative Comparative Analysis Thursday - Apr 21, 2022 D6P1 09:00-12:00 Econometric Modeling D6P2 13:00-16:00 Project Presentations * The time is subject to change. Please check for updates prior to the course. *All daily sessions will take place between 9:00 – 12:00 and 13:00 – 16:00 unless noted otherwise. |
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Learning objectives |
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| At the end of the course, students should be able to:
▪ Discuss the theories and methods that were presented in class and covered by the readings ▪ Design theoretically valid and methodologically rigorous quantitative studies ▪ Develop instruments for quantitative data collection ▪ Identify and assess data sources and data collection methods for quantitative studies ▪ Assess the reliability and validity of measures ▪ Demonstrate an understanding of quantitative data analysis techniques ▪ Interpret analytical results from quantitative studies ▪ Articulate in writing a formal description of quantitative research design and analysis |
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Exam |
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Individual take-home 15 pages written exam together with a research proposal presentation will form the basis for evaluating students’ performance. The written exam and the presentation will have equal weight in the course grade. Grading is based on the standard 7-step scale. A passing grade on two individual 5 pages written homework assignments is a prerequisite for taking the exam.
The exam will take the form of an individual take-home 15 pages written exam that is designed to foster deep reflections on the quantitative research methods covered in the course. The exam involves data analysis procedures in SPSS and SmartPLS (or another structural equation modeling software of your choice). All work must be original material that is produced individually. The exam will be distributed after the last class of the course and will be due in one week. Re-take exam, if necessary, will be administered about a month later. |
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Other |
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Start date |
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| 23/03/2022 | ||
End date |
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| 21/04/2022 | ||
Level |
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| PhD | ||
ECTS |
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| 6 | ||
Language |
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| English | ||
Course Literature |
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| Textbooks ▪ DeVellis, R. F. Scale Development: Theory and Applications (Vol. 26), Sage Publications, 2011. ▪ Pedhazur, E. J., and Schmelkin, L. P. Measurement, Design, and Analysis: An Integrated Approach, Psychology Press, 1991. ▪ Hair Jr, J. F., Hult, G. T. M., Ringle, C., and Sarstedt, M. A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM), Sage Publications, 2016. Supplementary Readings: See reading list under a separate cover. Additional articles and resources will be provided on a need-to basis. |
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