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Psychologist scientifically validating a recruitment test with statistical data
SCIENTIFIC CONSTRUCTION & VALIDATION

Assessments: built & validated

Poorly constructed tests
Rigorous psychometric validation
Optimal reliability coefficients
Proven scientific methodology
Non-validated tests eliminated
International psychometric standards

Why is the scientific validation of your tests crucial?

As an HR professional, you know that bad hires are costly for your company. That's why our SIGMUND tests are scientifically validated according to the most rigorous international psychometric standards.

Our validation indicators guarantee reliable assessments that significantly reduce recruitment errors and allow you to select the best candidates with confidence.

Discover the key concepts of validation in 5 minutes
Statistical symbols representing Content Validity

Content Validity

Definition: Content validity measures whether the test questions adequately cover the entire subject they claim to evaluate.

Why it's useful: It ensures that the test evaluates all relevant aspects of the targeted competency or trait.

For SIGMUND tests:

0.8
Concordance coefficient > 80%
Results on the Criterion Validity of SIGMUND test

Criterion Validity

Definition: Criterion validity evaluates how well test results correlate with another reliable indicator of the same competency or trait.

Why it's useful: It helps predict whether test results truly represent candidates' actual performance.

For SIGMUND tests:

0.6
Correlation coefficient (r)
A statistician presenting the Construct Validity of a SIGMUND test

Construct Validity

Definition: Construct validity examines whether the test measures the theoretical concept it is supposed to evaluate.

Why it's useful: It ensures that the test measures the right concept and not something different.

For SIGMUND tests:

0.7
Factorial validity coefficient
Psychologists working on the Reliability of Sigmund tests

Reliability

Definition: Reliability measures the consistency of test results. A test is reliable if it produces similar results under similar conditions.

Why it's useful: It ensures that test results are stable and reproducible, therefore credible.

For SIGMUND tests:

0.8
Cronbach's alpha coefficient
Statisticians working on the Sensitivity of Sigmund tests

Sensitivity

Definition: The sensitivity of a test refers to its ability to detect small differences between the individuals being evaluated.

Why it's useful: This is important to distinguish skill levels or similar traits among candidates.

For SIGMUND tests:

50%
Explained variance
A psychologist presents the statistical validation results of Fairness of SIGMUND test

Fairness

Definition: Fairness verifies that the test does not favor or disadvantage certain groups of people, for example due to their gender, age, or cultural background.

Why it's useful: It ensures that all candidates have an equal chance of succeeding on the test, regardless of their personal characteristics.

For SIGMUND tests:

p < 0.05
Absence of significant differences

Explore the SIGMUND Test Catalog

Discover our comprehensive range of scientifically validated psychometric assessments.

View the Test Catalog Browse Tests by Category