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Validity
Measuring what you think.
Reliability
How close to the true score are we likely to be.
Practicality
Does it make sense to apply it to this setting? Is it worth it? Related to utility.
Cross-Sectional Fairness
Is it accurate for someone in this group? Absence of test or assessor biases.
Correlation
Is the degree of the relationship between 2 variables.
No Correlation
No relationship; no pattern, random, no meaningful predictors.
Construct Validity
Asks if a quality is measurable and if it is an accurate measure.
Criterion Related Validity
Relationships between scores and other measures; do the scores predict performance on a criterion?
Concurrent Validity
Can predict score now; measures scores against established tests.
Predictive Validity
Can predict future scores or performance based on current measures.
Hit Rate
Hits/(hits + misses); measures prediction accuracy.
False Positives
Predict high/pass/trait but not accurate.
False Negatives
Predict absence of something but it's actually present.
Reliability Coefficient
A stat that quantifies reliability, ranging from 0 (not reliable) to 1 (reliable).
Test Retest
Correlates scores from the same test given at different times.
Alternate Forms
Same content tapped differently but equally; assess score correlation between versions.
Interscorer Reliability
Same people assessed by different administrators.
Split Half Reliability
Divide test into two halves and correlate scores.
Coefficient Alpha
Mean of all possible split halves.
Inter-Item Consistency
Degree of correlation among all items in a test.
Convergent Validity
Scores highly correlate with other tests as expected.
Discrimination Validity
Scores show little or no relationship with irrelevant measures.
Negative Correlation
An inverse relationship between two variables.
Positive Correlation
A direct relationship where higher values of one variable relate to higher values of another.
Strong Correlation
The closer to -1 or +1, the stronger the relationship, better prediction accuracy.
Weak Correlation
Scores closer to 0 indicate a weak relationship, making predictions less accurate.