1. Chapter 7 Cooper and Schindler
Measurement
Chapter 7
Cooper and Schindler

2. Measurement
Consist of assigning numbers to empirical events in compliance with a set of rules
The definition implies that measurement is a three-part process
Selecting observable empirical events
Using numbers or symbols to represent aspects of the events
Applying a mapping rule to connect the observation to the symbol
Example
Studying people who attend an auto show where all of the year’s new models are on display
Gender
Styling characteristics

3. Characteristics of Measurement
Gender
Styling Characteristics
A B C D E
A B C D E
Desirability
of styling to
show attendees
A-E
Empirical
Observations
Gender
of show
attendees
A-E
Assign
5 if Very Desirable
4 if Desirable
3 if neither
2 if undesirable
1 if Very Undesirable
Mapping Rule
Assign
“M” if male
“F” if female 1 2 4 3 5 M F
(1 through 5)
Symbol

4. What Is Measured? (I) Concepts
Objects
Include the things of ordinary experience, such as tables, people, books and automobiles
Also include things that are not as concrete, such as genes, attitudes, neutrons and peer-group pressures
Properties
Are the characteristics of the objects
Physical properties
Psychological properties
Social properties
Researchers measure indicants of the properties of objects

5. What Is Measured? (II) It is not easy to measure properties
Age, Years of experience, Number of calls per week
It is not easy to measure properties
Motivation to succeed, ability to stand stress, problem-solving ability, and persuasiveness
There is often disagreement about how to operationalize the indicants
Not only is it a challenge to measure such constructs, but a study’s quality depends on what measures are selected or constructed, and how they fit the circumstances

6. Scale Classifications
Employ the real numbers systems
The most accepted basis for scaling has three characteristics
Number are ordered (Order)
Differences between numbers are ordered (Distance)
The number series has a unique origin indicated by the number zero (Origin)

7. Measurement Scales Nominal Ordinal Interval Ratio No order, or origin
Determination of equality
Ordinal
Order but no distance or unique origin
Determination of greater or lesser values
Interval
Both order and distance but no unique origin
Determination of equality of intervals or differences
Ratio
Order, distance, and unique origin
Determination of equality of ratios

8. Nominal Scales
Partition a set into categories that are mutually exclusive and collectively exhaustive
Counting is the only arithmetic operation
Only labels and have no quantitative value
No order or distance relationship and have no arithmetic origin
No general used measure of dispersion
Several tests for statistical significance may be utilized
Chi-square test
For measures of association, phi, lambda, or other measure may be appropriate

9. Ordinal Scales
Include the characteristics of the nominal scale plus an indicator of order
Ordinal scales are possible if the transitivity postulate is fulfilled.
An extension of the ordinal concept occurs when more than one property is of interest
Add and average ranks is technically incorrect
Use a multidimensional scale
Have another difficulty when combining the rankings of several respondents
Convert the ordinal scale into an interval scale
Thurstone’s Law of Comparative Judgment

10. Ordinal Scales
Examples of ordinal scales include opinion and preference scales
Paired -comparison techniques
Ordinal scales have only a rank meaning
Statistical measures
Central tendency
median
Dispersion
Percentile or quartile
Correlation
Rank-order methods
Statistical significance
Nonparametric methods

11. Interval Scales
Has the powers of nominal and ordinal plus one additional strength
Incorporates the concept of equality of interval
Calendar time is interval scales
Zero time and zero degree(Centigrade and Fahrenheit) are arbitrary origin
Many attitude scales are presumed to be interval
Thurstone’s differential scale was an early effort to develop such a scale
Statistical measures
Central tendency (Arithmetic mean)
Dispersion (Standard deviation)
others (Product moment correlation, t-tests, and F-tests)

12. Ratio Scales
Incorporate all of the powers of the previous ones plus the provision for absolute zero or origin
Represent the actual amounts of a variable
Examples are weight, height, distance, and area
In behavioral sciences, few situations satisfy the requirement of the ratio scale(Psychophysics offering some exceptions)
In business research, we find ratio scale in many areas (money values, population counts, distances)
Statistical measures
All statistical mentioned up to this point
Multiplication and division
Geometric mean, coefficients of variation

13. Sources of Measurement Differences
The respondent as an error source
Situation factors
The measurer as an error source
Instrument as an error source

14. Sound Measurement Validity Reliability Practicality Content validity
Criterion-related validity (Concurrent validity, Predictive validity)
Construct validity
Reliability
Stability (Test-retest)
Equivalence (Parallel forms)
Internal consistency (Split-half, KR-20, Cronbach’s alpha)
Practicality
Economy
Convenience
Interpretability

15. Criteria for Evaluating a Measurement Tool
Validity
Refer to the extent to which a test measures what we actually wish to measure
Reliability
Has to do with the accuracy and precision of a measurement procedure
Practicality
Is concerned with a wide range of factors of economy, convenience, and interpretability

16. Validity Internal and external Research Instrument internal validity
Measure what it is purported to measure
Does the instrument really measure what its designer claims it does?
Three major forms
Content validity
Criterion-related validity
Concurrent validity
Predictive validity
Construct validity

17. Content Validity
The extent to which it provides adequate coverage of the topic under study
Determination of content validity is judgmental and can be approached in several ways
Through a careful definition of the topic
Use a panel of persons to judge

18. Criteria-Related Validity
reflects the success of measures used for prediction or estimation
Predict an outcome
Estimate the existence of a current behavior or condition
Predictive and concurrent validity differ in time perspective
An opinion questionnaire that correctly forecasts the outcome of a union election has predictive validity
An observational methods that correctly categorizes families by current income class has concurrent validity
Any criteria measure must be judged in terms of four qualities: relevance, freedom from bias, reliability, availability

19. Construct Validity
One may wish to measure or infer the presence of abstract characteristics for which no empirical validation seems possible
Attitude scales
Aptitude tests
Personality tests
Example
Measuring the effects of ceremony on organizational culture
Ceremony was operationally defined would have to correspond to an empirically grounded theory
Convergent validity
Discriminant validity

20. Reliability
A measure is reliable to the degree that it supplies consistent results
Reliability is a contributor to validity and is a necessary but not sufficient condition for validity
Reliability is concerned with estimates of the degree to which a measurement is free of random or unstable error

21. Stability
A measure is said to be stable if you can secure consistent results with repeated measurements of the same person with the same instrument
Test-retest

22. Equivalence
Considers how much error may be introduced by different investigators (in observation) or different samples of items being studied (in questioning or scales)
Equivalence is concerned with variations at one point in time among observers and samples of items
Interrater reliability may be used to correlate the observations or scores of the judges and render an index of how consistent their ratings are

23. Internal Consistency
Use only one administration of an instrument or test to assess consistency or homogeneity among the items
Split-half techniques
Spearman-Brown correction formula
The test splitting may influence the internal consistency coefficient
Kuder-Richardson Formula 20
Cronbach’s Coefficient Alpha