Principal speaker
Associate Professor Sama Low Choy
Do you have questions about the meaning of SEM, compared to other options available? Do you wish to refine your understanding of SEM issues, so that you can better interpret & critically assess research in your field that uses SEM? Then this workshop is for you!
This is a flipped classroom presentation, which hopes that attendees have read some of the set paper (Gefen et al, 2000). The presenter will guide discussion to better understand SEM, by comparing the analysis of the same data via regression or two different kinds of SEM. If time permits, and there is sufficient interest, we may refer to a recent review of SEM (Tarka, 2018) regarding its "usefulness and controversies in the social sciences".
Format: Interactive - will involve participation and discussion in groups.
Prerequisite: A sound knowledge of SEM. Please run an SEM in a statistical package (such as AMOS for SPSS, or lavaan for R), either using your own data, or one of the datasets included in the online help/tutorials or other texts.
Software requirements: This workshop does not require software.
Pedagogy:
This is learner-led education, with a "flipped classroom" approach, which means that participants are asked to do some preparation which is used as a basis for the material presented. The material will be structured around questions raised by participants (see preparation below). If very few questions are raised, then this will be a very short session!
Preparation:
Please read Gefen et al (2000), which has been cited nearly 8,000 times. In the week prior to the workshop, you will be sent a link to an online form, and asked to upload (1) a quotation from the paper (and page number) that you'd like to explore more in the workshop; (2) a citation of another paper that you have found useful for explaining application, interpretation or issues of SEM, in your field.
We will also invite you to do the same with Tarka (2018), noting that this is a much more involved paper. Thus I suggest that you focus on the latter sections addressing current issues & debates, rather than starting with the history -- this is an opportunity to seek helpful guidance to understand key points.
Gefen, D., Straub, D., & Boudreau, M. C. (2000). Structural equation modeling and regression: Guidelines for research practice. Communications of the association for information systems, 4(1), 7.
Tarka, P. (2018). An overview of structural equation modeling: its beginnings, historical development, usefulness and controversies in the social sciences. Quality & quantity, 52(1), 313-35
Event categories
RSVP
RSVP on or before Friday 23 April 2021 07.59 am, by email RED@griffith.edu.au , or via https://events.griffith.edu.au/yq8NmN