Scientific & Statistical Reasoning – Article summary (UNIVERSITY OF AMSTERDAM)
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Cohen on the science of psychological measurement” - Article summary
A utility analysis refers to 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. It is done in order to see whether the benefits of using a test outweigh the costs of that test. The objective of a utility analysis determines the required information (1) and the specific methods that have to be used (2).
One method of utility analysis is expectancy data. This is converting the test data to an expectancy table. It can provide a likelihood that a test taker will score within some interval of scores on a criterion measure. Taylor-Russel tables provide an estimate of the extent to which inclusion of a particular test in the selection system will improve selection. It gives an increase in base rate of successful performance that is associated with a particular level of criterion-related validity.
The selection ratio is a numerical value that reflects the relationship between the number of people to be hired and the number of people available to be hired. The base rate refers to the percentage of people hired under the existing system.
Top-down selection is a process of awarding available positions to applicants whereby the highest scorer is awarded the first position. A downside of top-down selection is that this may lead to unintended discriminatory effects.
Hit | A correct classification |
Miss | An incorrect classification |
Hit rate | The proportion of people that an assessment tool accurately identifies as possessing or exhibiting a particular trait, ability, behaviour or attribute. |
Miss rate | The proportion of people that an assessment tool inaccurately describes as possessing or exhibiting a particular trait, ability, behaviour or attribute. |
False positive | A specific type of miss whereby an assessment tool falsely indicates that the test taker possesses a trait. |
False negative | A specific type of miss whereby an assessment tool falsely indicates that the test taker does not possess a trait. |
One limitation of the Taylor-Russell tables is that the relationship between the predictor and the criterion must be linear. Naylor-Shine tables make use of the differences between the means of the selected and unselected groups to derive an index of what the test is adding to the established procedures. It determines the increase in average score on a criterion measure.
The Brogden-Cronbach-Gleser formula calculates the dollar amount of utility gain resulting from using a specific selection instrument. It uses the following formula:
utility gain=NTrxySDyZm-NC
N represents the number of applicants selected per year. T represents the average length of time in the position. Rxy represents the criterion-related validity coefficient for the given predictor and criterion. SDy represents the standard deviation of performance of employees. Zm represents the standardized mean score on the test for selected applicants. C represents the cost of the test for each applicant.
Productivity gain refers to an estimated increase in work output. It helps estimate the percent increase in output expected through the use of a particular test.
Instrument | Advantage | Disadvantage |
Expectancy table or chart | Easy to use graphical display. It aids in decision making regarding a specific individual or a group of individuals scoring in a specific range. | Dichotomizes performance into successful and unsuccessful |
Taylor-Russell table | It shows the relationship between selection ratio, criterion-related validity and existing base-rate. It aids decision making with regard to test use and recruitment to lower the selection ratio. | Relationship between predictor and criterion must be linear and it does not indicate the likely average increase in performance with use of test. It is difficult to identify a criterion value to separate successful and unsuccessful performance. |
Naylor-Shine table | It provides information needed to use the BCG formula and does not dichotomize criterion performance. It can show average performance gain or show selection ratio needed for a particular performance gain. | It overestimates utility unless top-down selection is used. It can be difficult to interpret in practical terms as it is based on standardized units. |
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Scientific & Statistical Reasoning – Article summary (UNIVERSITY OF AMSTERDAM)
Scientific & Statistical Reasoning – Summary interim exam 5 (UNIVERSITY OF AMSTERDAM)
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Scientific & Statistical Reasoning – Summary interim exam 5 (UNIVERSITY OF AMSTERDAM)
This bundle contains everything you need to know for the fifth interim exam for the course "Scientific & Statistical Reasoning" given at the University of Amsterdam. It contains both articles, book chapters and lectures. It consists of the following materials:
...Scientific & Statistical Reasoning – Article summary (UNIVERSITY OF AMSTERDAM)
This bundle contains all the summaries for the course "Scientific & Statistical Reasoning" given at the University of Amsterdam. It contains the following articles:
- “Borsboom & Cramer (2013). Network analysis: An integrative
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