Texas A&M University--Central Texas
“Selection Decision Making” - Chapter 11 (6th ed.)
Key Student Study Guide Key
· When it comes to making selection decisions, HR professionals generally establish selection procedures, ensure relevant laws and regulations are being followed, and represent the interest of employees to management.
o Who is generally responsible for the initial assessment, substantive methods, if any are used, and background investigations? HR Department
o Who generally makes discretionary hiring decisions? managers
o What source provides guidelines for record keeping for protected class information (e.g., sex, race, etc.) within all major job categories? Uniform Guidelines on Employee Selection Procedures
· Validity refers to the relationship between predictor and criterion scores.
o A useful predictor of job performance could have a validity coefficient sign that is either positive or negative.
o When deciding whether or not to use a new predictor, the validity coefficient, the base rote, and the selection ratio should be considered in combination, not independently.
· Utility refers to the expected gains to be derived from using a predictor.
o How is the usefulness of a predictor is determined ?
o What is the most fundamental concern regarding utility analysis ?
o Statistical significance is stated as a probability and indicates a given predictor’s chances of yielding similar validity coefficients with different sets of applicants.
o Practical significance is the value the predictor adds to the prediction of job success.
o “Hiring success gain” is optimized when there is a high validity coefficient, high base rate and low selection ratio. (Taylor-Russell tables are effective decision making tools in that they allow simultaneous consideration of a predictor’s base rate, selection ratio and validity.)
In general, the greater the correlation of a given predictor with other predictors of a criterion, the more it indicates similarity of measurement instead of identifying different characteristics.
o All other things being equal, if a selection specialist must decide between two predictors, the one that causes the least adverse impact would be the best choice. [best or worse] choice.
o The economic gain formula provides an estimate of the economic gain derived from using a predictor versus random selection methods.
v When using the economic gains formula, if the validity of the selection procedures is increased with no change in cost, the economic gain value should increase.
Cut scores should be consistent with the normal expectations of acceptable proficiency within the workforce
o In assessing cutoff scores, a “false negative” is an applicant who is assessed as not likely to succeed, but who would have been successful if hired.
o A “false positive” is one who is assessed as having competence to succeed, but who would have been an unsuccessful performer, if hired.
o “True positive” and “true negatives” are oftentimes called “hits” because they are correct in assessing workplace success; they both “hit” the assessment target.
o Higher cut scores result in fewer false positives [false positives/negatives?].
v If cutoff scores are lowered, it will most likely affect the hiring results by providing fewer [more/fewer?] false negatives and more false positives.
v Remember that hiring false positives [false positives/negatives?] will likely result in problems ranging from low customer service and increased scrap rates and accidents. The result could even be death. Further, rejecting false negatives may result in loss of competitive advantage and adverse impact problems.
v When the cost of making false positive errors is extremely high, it is best to use a minimum competency approach.
o Knowledge of a predictor’s validity is used to help establish cutoff scores when the methods employed to set the scores are criterion-related
o If a cutoff score is based on organizational needs, such as vacancies to be filled, demand for labor, and AA requirements, the method for setting the cutoff score is most liked to be norm-referenced. The top-down approach is the traditional selection cut score method and will generally yield the highest validity and utility.
· When using multiple predictors and a compensatory model to make hiring decisions, and the variables serving as predictors are measured in different units of measure, the most advisable first step is to convert raw scores into standard scores.
· Multiple regression methods for assessing job applicants will be more precise than unit weighting when:
o there is a small number of predictors; [large or small?]
o low correlations between predictors; [high or low?]
o high correlation of each predictor with the criterion; and, [high or low?]
o large sample size. [large or small?]
· Discretionary decisions involve making a final selection from a group of finalists
o Ranking is a very popular method to make the final selection decision.
· Rejected applicants are more likely to recommend an organization to others when they are given an explanation for their rejection; however, there is no obligation to do so.