Expert answer:Planning and staffing week 2-2

Solved by verified expert:PLEASE RESPOND TO THIS, I MUST COMPLETE A PEER REVIEW ON THE BELOW. Thanks Please demonstrate critical thinking abilities. No fewer than 250 words for post. Do not summarize the post and/or course concept(s), but perhaps comment on concepts directly applicable to your workplace. For this response, should outside sources be used to support the content within the postings, proper in-text citations and correctly formatted references should be prepared consistent with the APA (6th edition). The list of references should be physically positioned at the end of the postings. Hello, thank you! Please use critical thinking, good grammar and do not plagiarized, thanks. 1. As the new HR generalist for Lyssna Audio, you are asked to implement a structured interview. Managers want to know if you think it will select future high performers. How do you show this using criterion validation. Gatewood et al (2011) state that criterion validation is to be used to “address the issue of ‘test fairness’ or the comparative performance of various groups on a particular test.” Validity is of special importance, as it refers to “how accurately a selection system predicts performance on the job” (“Structured,” 1999). Validity directly relates to another term: reliability. Reliability refers to “how consistent results are over time and on a wide range of people” (“Structured,” 1999). Whereas unstructured interviews tend to allow interviewers the freedom to ask whatever questions (permissible by law) that they want, they don’t always involve more in-depth questions that might explain why candidates respond the way they do – leaving employers essentially in the dark with respect to how these potential employees might perform (“Structured,” 1999). If a system is more structured, it is also more reliable; Two different people interviewing the same candidate(s) should ideally receive the same responses (“Structured,” 1999). While unstructured interviews explain only 14 percent of an employee’s performance, structured interviews give both the employer and candidate a better experience and are generally regarded as the most fair (Bock, 2015). Using criterion validation, it would be easy to determine the relative fairness of structured interviews (a set assortment of questions) as opposed to an unstructured interview, where the employer could essentially be all over the place with their inquiries. References: Bock, L. (2015). Here’s Google’s secret to hiring the best people. Retrieved from https://www.wired.com/2015/04/hire-like-google/ Gatewood, R., Field, H., & Barrick, M. (2011). Human resource selection (7th ed.). Mason, OH: South-Western Cengage Learning. Structured interviews may be more valid and more reliable. (1999). Retrieved from http://www.workforce.com/1999/10/15/structured-interviews-may-be-more-valid-and-more-reliable/ 2. As the new HR generalist for Lyssna Audio, you are asked to implement a structured interview. Managers want to know if you think it will select future high performers. How do you show this using criterion validation? If I was asked to implement a structured interview, I would inform the managers it would select future high performers. A criterion usually serves as a definition of what is meant by employee success on the job. Criteria are defined by thoroughly studying the jobs for which a selection system is being developed. A wide array of variables might serve as criteria. Some criteria deal with issues such as absenteeism, turnover, and other organizational citizenship behaviors. Other criteria represent work related outcomes including error rates, number of good produced, dollar sales, amount of scrap produced in manufacturing tasks, and speed of performance (Gatewood, Field, Barrick, 2011). By using these criterion, managers can find the best employees who will increase work productivity and increase internal working relationships. Using the correct criterion will enable managers to identify what is important to the organization and address the needs of the organization by finding/hiring the best applicant. Gatewood, Field & Barrick. (2011). Human Resources Selection. 7th Edition. Mason, OH: south-Western. Cengage Learning. Yugo, J. (2015, Feb 5) Structured Interview: 4 Key Advantages to Using Them. Retrieved from Corvirtus: http://corvirtus.com/four-key-advantages-to-using-… to an external site.
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Part 2 Foundations of Measurement for Human Resource Selection
CHAPTER
3
Human Resource
Measurement in Selection
©2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.
Fundamentals of Measurement:
An Overview
• Questions Concerning Information Used in Selection
What types of information can be used?
Where does this information come from?
What characteristics should this information have in
order to be most useful for selection purposes?
• Remember: People are different
• Goal: Identify those who should be hired.
©2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.
3–2
The Nature of Measurement
• Measurement
The systematic application of pre-established rules
(or standards) for assigning numbers (or scores) to
the attributes or traits of an individual.



Rules provide the bases for clearly and consistently assigning
numbers to objects.
Attributes are external and internal qualities and abilities of
individuals assessed (or inferred) through direct or indirect
observation.
Numbers provide a convenient means for characterizing and
differentiating among job applicants.
©2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.
3–3
The Nature of Measurement (cont’d)
• Criterion Variables
A definition of what is meant by employee success on
the job.


Organizational issues: absenteeism, turnover, citizenship
behaviors
Work-related outcomes: error rates, goods produced, total
sales, scrap rates, speed of performance
• Criteria
Must be recognizable (definition)
Must be important to the job (relevance)
Must be appropriately assessed (measurement)
©2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.
3–4
The Nature of Measurement (cont’d)
• Predictor Variables
A measure of an employee attribute identified through
a job analysis as being important for job success

Tests, interviews, biographical data questionnaires,
application blanks, and assessment centers
• Requirements for Predictors
They must be relevant to the job
They must be appropriate ways to measure the
employee attributes identified as critical to job
success
©2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.
3–5
FIGURE 3.1 Hypothetical Distribution of Quantity of Wire
Baskets Produced by a Large Number of
Workers
©2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.
3–6
Scales of Measurement
• Precision of Measurement
Determines the number of distinct scores permitted
by the predictor and criterion used
Determines the meaningfulness of the numbers or
scores derived from our predictors and criteria
• Scale of Measurement
A means by which individuals can be distinguished
from one another on a variable of interest, whether
that variable is a predictor or a criterion
©2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.
3–7
Scales of Measurement (cont’d)
• Nominal Scale
Is composed of two or more mutually exclusive
categories.




All individuals having a common characteristic are assigned
to the same category or class.
Members in the same category or class are regarded as
being equivalent.
Individuals can belong to only one category or class.
Numbers can be given to individuals assigned to scale
categories; however, the numbers serve as labels and carry
no numerical meaning.
©2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.
3–8
FIGURE 3.2 Hypothetical Distributions of Trainees for
Two Different Criteria of Trainee Success
©2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.
3–9
Scales of Measurement (cont’d)
• Ordinal Scale
Ranks objects, such as individuals, from “high” to
“low” on some variable of interest.

Individuals are assigned a number representative of a
category, as on a nominal scale, but differences between the
numbers indicate the relative position of individuals for the
variable on which they are ranked.
Does not provide information on the magnitude of the
differences among the ranks.
©2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.
3–10
FIGURE 3.3 Example of an Ordinal Scale of Measurement
Ranking of Employees
At right are listed the names of your
ten subordinates. Read over the list
and then rank the individuals on their
quality of work completed in their jobs.
By “quality of work completed,” we
mean the minimum amount of rework
necessary to correct employee
mistakes. You should give the
subordinate you believe is highest in
quality of work performed a rank of
“1,” the employee next highest in
quality of work a “2,” the next a “3,”
and so on until you give a “10” to the
employee who is lowest in quality of
work completed.
©2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.
3–11
Scales of Measurement (cont’d)
• Interval Scale
Uses constant (equal interval) units of measurement
that represent meaningful rank-order differences with
respect to a normally-distributed characteristic
Has an arbitrary (but not absolute) zero point that is
set by convention
Is frequently used as either a predictor or a criterion
measure (rating scale) in selection studies
Allows data to be analyzed by many of the statistical
procedures important in personnel research
©2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.
3–12
FIGURE 3.4 Example of an Interval Scale Used in Rating
Employee Job Performance
©2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.
3–13
Scales of Measurement (cont’d)
• Ratio Scale
Has an absolute zero point
Has numerical values that can be added, subtracted,
multiplied, and divided to form comparison statements
for differences in individual values associated with the
measured characteristic
Is not often encountered in human resource selection
because selection measures are more often
psychological rather than physical in nature
©2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.
3–14
TABLE 3.1
General Characteristics of the Four Scales of
Measurement
©2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.
3–15
Characteristics of Selection Measurement
Standardization
Content
Administration
Standardization
of Measurement
Scoring
©2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.
3–16
Standardization of Selection Measurement
• Content
All persons assessed are measured by the same
information or content. This includes the same format.
• Administration
Information is collected the same way in all locations
and across all administrators, each time the selection
measure is applied.
• Scoring
Rules for scoring are specified before administering
the measure and are applied the same way with each
application.
©2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.
3–17
Measures Used in HR Selection
• Predictors
Measures used to decide whether to accept or reject
applicants for a specific job.

Background information
– Application forms
– Reference checks
– Biographical data questionnaires


Interviews
Tests
– Aptitude
– Achievement
– Ability
©2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.
3–18
Measures Used in HR Selection (cont’d)
• Criteria
Measures of behavior or performance on the job that
are used to evaluate the predictors used to forecast
performance.





Objective production data
Personnel data
Judgmental data
Job or work sample data
Training proficiency data
©2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.
3–19
TABLE 3.2
Factors to Consider when Choosing or
Developing Measures for Use in
HR Selection Research
1. What does the predictor measure?
2. Is the predictor cost-effective?
3. Has the predictor been “standardized”?
4. Is the predictor easy to use?
5. Is the predictor acceptable to the
organization? To management? To the
candidate?
6. Is the criterion relevant to the job for which
it is chosen?
7. Is the criterion acceptable to
management?
8. Are work changes likely to alter the need
for the criterion?
9. Is the criterion uncontaminated and free of
bias, so that meaningful comparisons
among individuals can be made?
10. Will the criterion detect differences among
individuals if differences actually exist
(discriminability)? Are meaningful
differences among individuals actually
scored with respect to the criterion?
11. Does the measure unfairly discriminate
against sex, race, age, or other protected
groups?
12. Does the measure lend itself to
quantification?
13. Is the measure scored consistently?
14. How reliable are the data provided by the
measure?
15. How well does the device measure the
construct for which it is intended (construct
validity)?
SOURCES: Arne Evers, Neil Anderson, and Olga Voskuijl, The Blackwell Handbook of Personnel Selection (London: Blackwell Publishers, 2005),
73–97 and 354–375; and Susana Urbina, Essentials of Psychological Testing (Hoboken, NJ: John Wiley, 2004), 64–116.
©2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.
3–20
Advantages of Existing Selection Measures
Use of existing measures is usually less expensive
and less time-consuming than developing new ones.
If previous research has been conducted, we will
have some idea about the reliability, validity, and
other characteristics of the measures.
Existing measures may be superior to what could be
developed in-house.
©2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.
3–21
Information Sources for Existing Measures
• Text and Reference Sources
Annual Review of Psychology
Research in Personnel and
Human Resources
Management
• Buros Mental Measurements
Yearbooks
Sixteenth Mental
Measurements Yearbook
(2005)
Tests in Print (TIP) I–VI
• Other Reference Sources
Tests: A Comprehensive
Reference for Assessments in
Psychology, Education, and
Business (Fifth Edition)
Test Critiques, Volumes I–XI
• Journals
Journal of Applied Psychology
(JAP)
Personnel Psychology
• Test Publishers
• Professional
Associations
©2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.
3–22
TABLE 3.3
Internet Sources for Information on Existing
Selection Measures
http://www.unl.edu/buros
Buros Center for Testing
http://www.proedinc.com
Pro-Ed Inc.
http://www.ets.org
Educational Testing Service
http://eric.ed.gov
Education Resources Information
Center
http://testpublishers.org
The Association of Test Publishers
http://www.apa.org
American Psychological Association
http://www.siop.org
Society of Industrial & Organizational
Psychologists
©2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.
3–23
Choosing an Existing Selection Measure
• Be sure you clearly and completely understand the
attribute or construct you want to measure and
chooses a means for assessing it.
• Search for and read critical reviews and evaluations
of an available measure (test).
• Order a specimen test and study any information
relative to its reliability, validity, fairness, intended
purpose, method of administration, time limits,
scoring, appropriateness for specific groups, and
norms.
• Lastly, decide if there are compelling arguments for
using this measure? Or, are there compelling
arguments against using it?
©2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.
3–24
Constructing New Selection Measures
• Analyzing the job for which a measure is being
developed
• Selecting the method of measurement to be used
• Planning and developing the measure
• Administering, analyzing, and revising the
preliminary measure
• Determining the reliability and validity of the revised
measure for the jobs studied
• Implementing and monitoring the measure in the
human resource selection system
©2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.
3–25
FIGURE 3.5 Checklist Used to Match Selection Methods
with Job Requirements for the Job of
Industrial Electrician
©2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.
3–26
Planning and Developing Specifications for
the Selection Measure
• Specifications for each required measure
considered should include:
Purposes and uses of the measure
Nature of the population for which the measure is
designed
How behaviors or knowledge, skills, abilities, and
other attributes (KSAOs) will be gathered and scored
Sampling designs and statistical procedures to be
used in selecting and editing items, questions, and
other elements of the measure
©2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.
3–27
FIGURE 3.6 What an Industrial Electrician Needs to
Know to Perform the Job
Knowledge of Principles of Electrical Wiring
• Reading schematic drawings
• Choosing appropriate gauges of wire for different electrical
applications
• Installing circuit-breaker panels
• Selecting electrical fuses for different electrical applications
• Installing electrical grounds
• Checking voltages in electrical receptacles
• Computing voltage drops for various lengths and gauges of wiring
• Using copper and aluminum wiring
©2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.
3–28
FIGURE 3.7 Form Used to Determine Item Budget for
Knowledge Topics in the Industrial
Electrician Test
NOTE: The knowledge topics listed in the chart were developed from the knowledge of principles of electrical wiring listed in Figure 3.6.
Cells in the chart show the number of test items devoted to specific knowledge topics for various types of knowledge information.
©2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.
3–29
Administering, Analyzing, and Revising the
Measure
• Psychometric Characteristics to Consider
The reliability or consistency of scores on the items
The validity of the intended inferences
Item fairness or differences among subgroups
©2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.
3–30
Determining Reliability and Validity
• Questions to Address
Are the scores on the selection measure
dependable for selection decision-making?
Is the selection measure predictive of job
success?
Does the test measure what we think it
measures?
©2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.
3–31
Interpreting Scores on Selection Measures
• Using Norms
The norm group should be relevant for the purpose it
is being used
Use local norms as opposed to norms based on
national data
Norms are transitory
In using normative information statistical methods are
employed to aid interpretation of what a test score
means
©2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.
3–32
Using Percentiles
• Percentile Scores
Show the percentage of persons in a norm group who
fall below a given score on a measure

The higher the percentile score, the better a person’s
performance relative to others in the normative sample
Are not percentage scores
• Misuses of Percentile Scores
A difference of percentile points may not indicate a
real difference in people; the difference may be due to
chance, resulting from unreliability of the test
Percentile scores are based on an ordinal scale of
measurement, not a ratio scale
©2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.
3–33
FIGURE 3.8 Illustration of How Percentile Norms Are
Frequently Reported in Test Manuals
©2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.
3–34
Using Standard Scores
• Standard Scores
Represent adjustments to raw scores, so it is possible
to determine the proportion of individuals who fall at
various standard score levels
Indicate, in common measurement units, how far
above or below the mean score any raw score is
• Types of Standard Scores
z scores show distance from the normative group
mean in standard deviation units.
T scores are adjusted so that all T scores are positive
Stanine scores rank order scores from lowest to
highest
©2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.
3–35
Computing z Scores
• The formula for computing z scores is:
©2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.
3–36
FIGURE 3.9 Relationships Among the Normal Curve,
Percentiles, and Standard Scores
©2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.
3–37
Key Terms and Concepts
• Measurement
• Attributes
• Criterion
• Predictor
• Nominal scale
• …
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