The usefulness or practical value of testing to improve efficiency
Factors that affect a test's utility
Psychometric soundness
Costs
Benefits
Psychometric soundness
Refers to the reliability and validity of a test
Reliability
Tells us something about how consistently a test measures what it measures
Validity
Tells us something about the practical value of the information derived from scores on the test
Costs (in the context of test utility)
Disadvantages, losses, or expenses in both economic and non-economic terms
Costs related to testing
Purchasing a particular test
Purchasing a supply of blank test protocols
Computerized test processing, scoring, and interpretation from the test publisher or some independent services
Other testing costs
Payment to professional personnel and staff associated with test administration, scoring and interpretation
Facility rental, mortgage, and/or other charges related to the usage of the test facility
Insurance, legal, accounting, licensing, and other routine costs of doing business
Non-economic costs
Such as "loss of confidence" or costs in terms of loss
Benefits
Profits, gains, or advantages, both economic and non-economic
Benefits of testing
Proper recruitment of personnel
Increase in quality performance of workers
Good work environment in admission programs
Utility analysis
A family of techniques that entail a cost-benefit analysis designed to yield information relevant to a decision about the usefulness and/or practical value of a tool of assessment
Methods of utility analysis
Expectancy data
Taylor-Russel table
Naylor-Shine tables
Brogden-Cronbach-Gleser formula
Decision theory
Expectancy data
Provides an indication of the likelihood that a test-taker will score within some interval of scores on a criterion measure
Taylor-Russel table
Used to calculate the utility gain resulting from the use of a particular selection instrument under specified conditions
Naylor-Shine tables
Used to calculate the dollar amount of a utility gain resulting from the use of a particular selection instrument under specified conditions
Utility gain
An estimate of the benefit (monetary or otherwise) of using a particular test or selection method
Productivity gain
An estimated increase in work output
Decision theory
Provides guidelines for setting optimal cutoff scores
Factors considered in decision theory
Pool of job applicants
Complexity of the job
Cut scores in use
Cut score
A reference point derived as a result of a judgement and used to divide a set of data into two or more classifications, with some action to be taken or some inference to be made on the basis of these classifications
Relative cut score
A reference point in a distribution of test scores used to divide a set of data into two or more classifications that is set based on norm-related considerations rather than on the relationship of test scores to a criterion
Fixed cut score
Typically set with reference to a judgement concerning a minimum level of proficiency required to be included in a particular classification
Multiple cut scores
The use of two or more cut scores with reference to one predictor for the purpose of categorizing test takers
Multiple hurdle
A cut score is in place for each predictor used, and the achievement of a particular cut score on one test is necessary in order to advance to the next stage of evaluation in the selection process
Angoff method
Judgements of experts are averaged to yield cut scores for the test
Known groups method
A cut score is set on the test that best discriminates the two groups' test performance
IRT-based methods
Cut scores are typically set based on test takers' performance across all the items on the tests, with each item associated with a particular level of difficulty
Bookmark method
Typically used in academic applications, where the bookmark serves as the cut score
Method of predictive yield
A technique for setting cut scores which took into account the number of positions to be filled, projections regarding the likelihood of offer acceptance, and the distribution of applicant scores
Discriminant analysis
Provides insight regarding the relationship between identified variables and two naturally occurring groups