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.