WPS HW P2

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CHAPTER 6

Human Resource Measurement in Selection

Learning Objectives

Understand the role of measurement in human resource (HR) selection.

Explain four different scales of measurement and the conclusions that can be legitimately drawn from data produced by each scale.

Understand why standardized measures are important to use in HR selection.

Know how to research a published test being considered for use in HR selection.

Understand the fundamentals in developing and implementing a selection procedure.

Interpret the meaning of percentile norms.

Fundamentals of Measurement: An Overview

An assumption in selection decision making is that information is available for making these decisions. But

What types of information can be used?

Where does this information come from?

What characteristics should this information have to be most useful?

This chapter specifically focuses on:

the basics of psychological measurement as they apply to HR selection

locating, developing, and interpreting measures commonly used in HR selection

The Role of Measurement in HR Selection

The Nature of Measurement

From the perspective of HR selection:

HR measurement involves the systematic application of rules for assigning numbers to objects – usually people – to represent the quantities of a person’s attributes or traits

Rules suggest that the basis for assigning numbers is clearly specified and consistently applied – it is important that different users who use a test administer it under the same conditions and score it in the same manner as all other users

Physical attributes – gender – can be assessed through direct observation

Psychological attributes (constructs) – conscientiousness, intelligence – are not directly observable and must be inferred from a score – numbers or units of measurement

The Role of Measurement in HR Selection

The Nature of Measurement

Criteria and predictors in selection research:

Identification of two types of variables is critical:

Criterion – measure of what represents successful performance on a job (supervisory ratings of work performance)

Predictor – a measure (of employee WRCs) used to forecast or predict the likelihood of job candidates’ success on a job

The Role of Measurement in HR Selection

The Nature of Measurement

Measurement and individual differences:

Measuring individual differences helps identify those individuals who should be hired for a job

Figure 6.1 shows a hypothetical distribution of quantity of output per worker for a large number of workers:

Individual employees differ in their levels of productivity

Relatively few produce a very large or very small number of baskets

We need a selection procedure that will predict productivity

The Role of Measurement in HR Selection

Scales of Measurement

A means by which individuals are distinguishable from one another on a variable such as a predictor or criterion

Predictor or criterion variables can differ dramatically in their precision – e.g. trainability

Figure 6.2 shows hypothetical distributions of trainees’ scores for two methods of measuring trainability

The Role of Measurement in HR Selection

Scales of Measurement

Four types of scales or levels of measurement exist:

Nominal – composed of two or more mutually exclusive categories (e.g., male or female)

Ordinal – rank-orders objects (individuals) from “high” to “low” (e.g., test scores as percentiles) (Figure 6.3)

Interval – uses constant units of measurement – differences between numbers take on meaning (Figure 6.4)

Ratio – has an absolute zero point – differences between numbers also have meaning (e.g., most scales involving physical measurements)

The degree of precision increases as we move from nominal to ratio scales (Figure 6.5)

The Role of Measurement in HR Selection

Standardization of Selection Measurement

The systematic application of pre-established rules or standards for assigning scores to the attributes or traits of an individual

A selection measure may provide information to be used as either a predictor or a criterion – differences in scores must be attributable to ability, and not to other factors

A predictor or criterion measure is standardized if it possesses:

Content – all people assessed are measure by the same information or content

Administration – information is collected the same way in all locations and across all administrations

Scoring – rules for scoring are specified before administering the measure and applied the same way with each scoring

Standardization of Selection Measurement

Measures Used in HR Selection

Criteria are employed as part of a research study designed to determine which selection procedures are related to job success and should be used in selection decision making – a validation study

Criterion measures help serve as a standard for evaluating how well predictors do the job they were intended to do

Predictors have a direct impact on decisions – a manager reviews an applicant’s scores

Criteria play an indirect role – which selection procedures should be used in making selection decisions

Standardization of Selection Measurement

Measures Used in HR Selection

Predictors or selection procedures:

Numerous types but in general the major types fall into three broad categories:

Background information – application forms, training and experience evaluations, reference checks, biographical data used to collect information

Interviews – employment interviews used to collect additional information

Tests – hundreds of tests have been used for selection purposes – aptitude, ability, achievement, personality

Standardization of Selection Measurement

Measures Used in HR Selection

Criteria or measures of job success:

Measurement methods used to collect data include the following:

Objective production data – physical measures of work

Personnel data – personnel records and files can serve as criterion measures

Judgmental data – performance appraisals or ratings

Job or work sample data – obtained from a measure of specific aspects of the work process or outcomes

Training proficiency data – how quickly and how well employees learn during job training activities

Standardization of Selection Measurement

Standards for Evaluating Selection Measures

Table 6.1 lists some of the factors to be considered when choosing or developing a selection measure

If a measure doesn’t meet these standards:

Determine whether you can adjust your data or the way you calculate the score itself so it will meet each measurement evaluation criterion

If this option is not viable, find or develop another, more suitable measure

The factors listed in Table 6.1 are not of equal importance

Standardization of Selection Measurement

Finding and Constructing Selection Measures

Once we know the criteria selection measures for successful work performance, the process of identifying and implementing the selection procedures may begin:

A consultant – industrial–organizational psychologist – is needed

Two choices:

We can locate and choose from existing selection measures

Construct our own

We might need to consider both options

Standardization of Selection Measurement

Locating Existing Selection Measures

Advantages of using existing measures:

Use of existing measures usually less expensive and less time-consuming than developing new ones

If previous research was conducted on these measures, we will have some idea about the reliability, validity, and other characteristics of the measure

Well-developed, existing measures often superior to what could be developed in-house

Standardization of Selection Measurement

Locating Existing Selection Measures

Information sources for existing measures:

Sources in print and on the Internet (Tables 6.2 and 6.3)

Text and reference sources – provide excellent reviews of predictors and other measures that have been used

Buros’ Mental Measurements Yearbooks – the most important source for information on tests for personnel selection

Other reference sources – journals, test publishers (levels A, B, C), professional associations

Standardization of Selection Measurement

Locating Existing Selection Measures

Suggestions for choosing an existing selection measure:

Be sure you clearly and completely understand the attribute or construct you want to measure – decide on the best means for assessing the attribute

Search for and read critical reviews and evaluations of the measure – Buros’ Mental Measurements Yearbook an excellent source

If a specimen set of the measuring is available, order and study it

Once steps 1-3 are completed, ask “are there more compelling arguments for using this measure? Or, are there compelling arguments against using it?”

Standardization of Selection Measurement

Constructing New Selection Measures

Developing of measures is a complex, resource-consuming process that usually requires expert advice

Consultants likely will be needed

Knowledge of the basic issues involved in selection measure development, validation, and application can help bridge any possible communications gap between the organization and the consultant

Standardization of Selection Measurement

Constructing New Selection Measures

Steps in developing selection measures:

Analyze the job for which a measure is being developed

Select the method of measurement to be used (Figure 6.6)

Plan and develop the measure (Figures 6.7 and 6.8)

Administer, analyze, and revise the preliminary measure

Determine the reliability and validity of the revised measure for the jobs studies

Implement and monitor the measure in the HR selection system

Standardization of Selection Measurement

Interpreting Scores on Selection Measures

Using Norms

To interpret the results of measurement, we need two pieces of information:

How others scored on the selection procedure

Validity of the selection procedure

Predictor scores of relevant others in groups are called norms

Keep the following in mind when using norms to interpret scores:

The norm group selected should be relevant

Accumulate and use local norms when appropriate

Norms are transitory – specific to the point in time when they are collected

Interpreting Scores on Selection Measures

Using Percentiles

Percentile scores show the percentage of a persons in a norm group who fall below a given score on a measure – a percental score is not a percentage score

The higher the percentile score, the better a person’s performance relative to others (Figure 6.9)

Percentile scores are useful in interpreting test scores, but are subject to misuse

Interpreting Scores on Selection Measures

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 – these scales indicate how far above or below the mean score any raw score is

Some of the more common are z, T, and stanine scores

z score the most common – can be obtained for all individuals for whom test score data are available

T scores – similar to z scores but adjusted so that all T scores are positive

Stanine scores – computed by rank-ordering scores from lowest to highest

Interpreting Scores on Selection Measures