AHS-P6-1. Examining the Factor Structure of the Trait Meta-Mood Scale While Accounting for Data Point Censoring
Fitsum Ayele1
Orei Odents1
Faculty Mentor: Kimberly Barchard, Ph.D.1
1College of Liberal Arts, Department of Psychology
ABSTRACT
Meta-mood experience refers to thoughts and feelings that serve to monitor, evaluate, and at times change mood. The Trait Meta-Mood Scale (TMMS) was designed to gauge meta-mood experience along three factors: Attention, Clarity, and Repair. Previous factor analyses have verified this three-factor structure. However, one study by Palmer and colleagues found strong support for a four-factor structure. In light of this discrepancy, the present study aimed to replicate Palmer and colleagues’ study in a new sample, comparing the models they used and determining which is best-fitting. We also aimed to correct the effect of data point censoring when estimating factor models. Data censoring occurs when researchers only have partial information about the value of a variable. 202 college undergraduates completed the TMMS during an online study. To compare the models, we relied on Akaike’s Information Criterion (AIC) and Bayesian Information Criterion (BIC). Results revealed that the four-factor model fit the data better than the three- and one-factor models tested. The first three factors corresponded to the previous Attention, Clarity, and Repair factors. The fourth factor was named Emotional Resilience because the items loading on this factor suggested resistance to negative emotional experiences. We suggest TMMS users calculate scale scores based on all four of these factors to provide a more detailed description of meta-mood experience. Limitations of the present study include the lack of absolute fit measures for the models tested. Future researchers should use other statistical programs to replicate (or extend) our study.
Date
- Nov 15 - 19 2021
- Expired!
Time
- 8:00 am - 6:00 pm
Labels
- AHS: Poster Session 6
Organizer
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The Office of Undergraduate Research
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Phone
702-895-4771 -
Email
our@unlv.edu -
Website
http://unlv.edu/our
Speakers
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Dr. Kimberly A. Barchard | College of Liberal Arts
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Fitsum A
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Orei Odents | College of Liberal Arts
Great presentation! The stats skills you developed in this project are a great investment in your educational journey. So proud of you!
Carrie
Excellent work!
Welcome to our presentation! We encourage you to engage with the material and leave feedback in the comments, letting us know any questions or thoughts you may have about the presentation. Thank you.