An Application of Logistic Regression in Identifying Target Populations Using TriMetrix EQ Variables
This study establishes relationships between several external variables based on demographic information obtained using the O*Net job classification model and the scales of the TTI Success Insights TriMetrix EQ assessment. The work uses a logistic regression modeling approach to derive statistically significant functional relationships between the TriMetrix EQ scales and membership in the job classification group of interest. ROC curve analysis is used to show the classification algorithm outperforms the standard random selection technique.
Thoughts on Current Consensus Views on Reliability and Validity in the Psychometric Assessment World
In many cases, organization such as the American Psychological Association, provide general guidelines without providing specific guidance. As an example, we discuss the concepts of acceptable levels of reliability coefficients, as measured by the so-called “alpha” coefficients where after several decades there remains a lack of consensus.
Emerging Trends & Traits Shaping the Industry 4.0 Talent Pipeline
To successfully navigate the Industry 4.0 environment (and beyond), organizations will need to integrate four different generations in their workforce and much more. TTI SI assessment data provides the cornerstone article in this 2019 Automation Alley State of Michigan peer-reviewed conference report.
Our Approach to Psychometric Assessment Validity and Reliability
The follow-on article discusses the specifics of the TTI Success Insights approach to addressing the American Psychological Association’s (APA) viewpoints toward and suggestions for measuring critical components of our assessments. The paper focuses on defining and explaining how TTISI is collecting evidence of validity and reliability.