1. Chapter Eight The Concept of Measurement and Attitude Scales

2. Chapter Eight Objectives
To understand the concept of measurement.
To understand the four levels of scales and their typical usage.
To explore the concepts of reliability and validity.
To become familiar with the concept of scaling.
To learn about the various types of attitude scales.
To examine some basic considerations in selecting a type of scale.
To realize the importance of attitude measurement scales in management decision making.
Chapter Eight

3. Measurement Process Measurement: Rule:
The Process of assigning numbers or labels to persons, objects, or events in accordance with specific rules for representing quantities or qualities or attributes.
The guide, method, or command that tells a researcher what to do.
Chapter Eight

4. Data Levels
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5. Nominal Data
Scales that partition data into “mutually exclusive and collectively exhaustive” categories.
Classification Type Data. Examples:
Yes or no questions;
Nouns in general
Gender;
Race / Ethnicity;
Occupation;
Text open-ended questions.
Analysis Approach:
Cross tabulations / Percentages;
Sums and frequency counts;
Can’t tell the relative value of responses.
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6. Ordinal Data
Scales that maintain the labeling characteristics of nominal scales and have the ability to order data.
Ranking Type Data Examples:
Best liked, worst liked;
Win, place, or show;
First, second, third;
Small, medium, and large;
Comparisons rankings -
“rank these movies from best to worst”
Analysis Approach:
Cross tabulations, sums and frequency counts;
Percentages, mode, mean for some types;
Can tell the relative order of responses
but not the distance between responses
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7. Interval Data
Scales that have the characteristics of ordinal scales, plus equal intervals between points.
Comparison Type Data Examples:
One a “1 to 10” scale;
Age, income, etc. as ranges
Red, blue, green
- if each rated from “1 to X” – for example.
Analysis Approach:
Standard deviation, variance, kurtosis;
Descriptive statistics - mean, median, mode;
Sums and ranged frequency counts;
Correlation;
Can tell the relative value of responses and
can tell the distance between responses.
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8. Ratio Data
Scales that have the characteristics of interval, plus a meaningful zero point.
Flat Numeric Type Data Examples:
Age = 50 (not an age range)
Income = $25,000 (not an income range)
Number of children: ________
Analysis Approach:
Standard deviation, variance, kurtosis
Descriptive statistics - mean, median, mode
Sums and ranged frequency counts
Pearson correlation, regression
Can tell the relative value of responses and
can tell the distance between responses and
how they relate to zero.
Chapter Eight

9. Reliability and Validity
Degree to which measures are free from random error and, therefore, provide consistent data. The extent to which the survey responses are internally consistent.
Validity:
Degree to which what the researcher was
trying to measure was actually measured.
Chapter Eight

10. Testing Reliability Test and Retest:
The ability of the same instrument to produce consistent results when used a second time under conditions as similar as possible to the original conditions.
Stability:
Lack of change in results from test to test.
Equivalent Form:
When two very similar forms of an instrument produce closely correlated results.
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11. Testing Reliability Internal Consistency:
The ability of an instrument to produce similar results when used on different samples during the same time period to measure a phenomenon.
Spilt Half:
A method of assessing the reliability of a scale by dividing the total set of measurement items in half and correlating the results.
Chapter Eight

12. Testing Validity Face:
The degree to which a measurement seems to measure what it is supposed to measure.
Content:
The representativeness, or sampling adequacy, of the content of the measurement instrument.
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13. Testing Validity Criterion Related:
The degree to which a measurement instrument can predict a variable that is designated a criterion.
Construct:
The degree to which a measurement instrument represents and logically connects, via the underlying theory, the observed phenomenon to the construct.
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14. Testing Validity Convergent:
The degree of correlation among different measures that purport to measure the same construct.
Discriminate:
The measure of the lack of association among constructs that are supposed to be different.
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15. Testing Validity Predictive:
The degree to which a future level of a criterion can be forecast by a current measurement scale.
Concurrent:
The degree to which another variable, measured at the same point in time as the variable of interest, can be predicted by the measurement instrument.
Chapter Eight

16. Reliability and Validity
Neither Reliable nor Valid
Highly Reliable but not Valid
Highly Reliable and Valid
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17. Measurement Scales Scaling Defined: Scaling Approaches:
Procedures for assigning numbers or symbols to properties of an object in order to impart some numerical characteristics to the properties in question.
Scaling
Defined:
Unidimensional:
Measures only one dimension of a concept, respondent, or object.
Multidimensional:
Measures several dimensions of a concept, respondent, or object.
Scaling
Approaches:
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18. Attitude Measurement Scales
Enduring organization of motivational, emotional, perceptual, and cognitive processes with respect to some aspect of a person’s environment.
Attitude
Defined:
Graphic Rating Scale:
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19. Attitude Measurement Scales
Important Not Important
Important Not Important
Odd Scale
Even Scale
Itemized
Rating
Scale:
Non-comparative Scale:
Scales in which judgement is made without reference to another object, concept, or person.
Comparative Scale:
Scales in which one object, concepts, or person is compared with another on a scale.
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20. Attitude Measurement Scales
Uses Comparative Scaling:
Put these fast food chains in order of preference:
McDonalds
Burger King
Taco Bell
Rank
Order
Scale:
Q-Sorting:
Measurement scale employing a sophisticated form of rank ordering using card sorts. Respondents each rank X number of items in order from best to worst by putting the cards representing the idea at hand into ranked piles. Then the piles with the most become the top choices. The procedure can be done many times to winnow down the choice to a top two or three.
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21. Attitude Measurement Scales
___Coke
Paired
Comparison:
___Pepsi
“Which drink do
you prefer:”
___Coke
___Sprite
___Pepsi
___Sprite
What features do you want in a car?
Sun roof ______
Leather ______
ABS Breaks ______
CD Player ______
Total points
Constant
Sum Scale:
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22. Attitude Measurement Scales
Semantic
Differential
Scale: -5 -4 -3 -2 -1
High Value +1 +2 +3 +4 +5
Staple
Scale:
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23. Attitude Measurement Scales
Likert
Scale:
Multiple
Choice
Scale: •
Multiple response
Single response
Controlled response
Check all that apply
Check only one
Check the top three
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24. Considerations in Selecting a Scale
Key Considerations:
The nature of the construct being measured;
The value and pitfalls of open ended questions;
Balanced vs. non-balanced;
Balanced - Scales that have the same number of positive and negative categories.
Non-balanced - Scales that are weighted toward one end or the other of the scale.
Forced vs. non-forced.
Having an odd Vs. even number of response choices.
Chapter Eight

25. Index Interval Data Measurement Scales Defined Nominal Data
Ordinal Data
Ratio Data
Reliability Defined
Scaling Tips
Scaling Measurement & Types
Testing Reliability
Testing Validity
Validity Defined
Index