Prove the Quality of Your Assessment
Third Party Assurance
ASI Certification helps ensure that the assessments you use or develop meet recognized standards for reliability, validity, fairness, and quality.
In addition to certification, ASI helps organizations identify the strengths and weaknesses of their assessments and provides specific, actionable recommendations for improvement.
Products that meet ASI standards earn the designation of being “ASI Certified” and are authorized to display the applicable ASI Certification Mark, demonstrating their commitment to achieving national standards
Assessment Certification Services
Theoretical Construct
Every high-quality assessment begins with a sound theoretical foundation. ASI evaluates the underlying theories, models, and research supporting an assessment to determine whether its design is grounded in established psychological, behavioral, educational, or organizational science. A strong theoretical basis increases credibility, supports meaningful interpretation of results, and provides confidence that the assessment measures concepts that are relevant, defensible, and useful in real-world applications.
Attribute Design
Well-designed attributes are essential to producing accurate and actionable assessment results. ASI reviews attribute definitions, scale construction, item alignment, and scoring methodologies to ensure that each attribute is clearly defined and effectively measured. Our analysis helps identify overlapping constructs, weak dimensions, and opportunities for improvement, resulting in assessments that provide greater clarity, differentiation, and value to users.
Data Integrity
Data constructs represent the underlying dimensions and relationships that an assessment is designed to measure. ASI evaluates the structural integrity of these constructs to determine whether assessment items group together as intended and accurately reflect the target attributes. Through advanced statistical analysis and expert review, we help ensure that assessment results are meaningful, interpretable, and aligned with the intended design of the instrument.
Data Reliability
Reliability is the foundation of every effective assessment. ASI's Data Reliability Analysis evaluates the consistency and stability of assessment results using recognized psychometric standards and statistical methods. Our review identifies strengths, weaknesses, and opportunities for improvement within individual scales and attributes. By ensuring reliable measurement, organizations can make hiring, development, coaching, and management decisions with greater confidence and accuracy.
Assessment Validity
- Construct Validity - is the degree to which a test measures what it claims to measure. Constructs are used to conceptualize latent variables. Our data measures correlations to the latent variable and to each other.
- Factor Analysis - is a method used to describe the variability observed. The method searches for joint variances with the goal of reducing redundant or ineffective variables.
- Criterion Validity - is the mathematical relationship between measurement critenon and a concurrent or predictive outcome.
- Structural Equation Modeling - is the use of mathematical models to establish the relationship between observable and latent or dependent variables.
Disparate Impact
- The 80% Rule: A measurement established to by the Department of Labor which states that the selection rate of the protected group should be at least 80% of the selection rate of the non-protected group.
- T-Test: is used to determine whether there is a significant difference in the scores of a protected group as compared to the dominant group.
- ANOVA: A statistical method used to determine if a significant difference exists between the mean scores of the protected class and the non-protected class groups results.