Chapter 13 Measuremen and Scaling Concept Slides.ppt
- 1. Chapter 13 Measurement and Scaling Concepts BUSINESS RESEARCH METHODS
- 2. 13–2 LEARNING OUTCOMES 1. Determine what needs to be measured to address a research question or hypothesis 2. Distinguish levels of scale measurement 3. Know how to form an index or composite measure 4. List the three criteria for good measurement 5. Perform a basic assessment of scale reliability and validity After studying this chapter, you should be able to
- 3. 13–3 What Do I Measure? • Measurement The process of describing some property of a phenomenon, usually by assigning numbers in a reliable and valid way. Measurement means assigning numbers or other symbols to characteristics of objects according to certain prespecified rules. The decision statement, corresponding research questions, and research hypotheses can be used to decide what concepts need to be measured. The numbers convey information about the property being measured. When numbers are used, the researcher must have a rule for assigning a number to an observation in a way that provides an accurate description.
- 4. • Numbers are usually assigned for two reasons: First, numbers permit statistical analysis of the resulting data Second, numbers facilitate the communication of measurement rules and results • Employee Satisfaction Level • (1-----agree 3----Neutral 5 ----disagree) Absenteeism 1 2 3 4 5 Meet deadlines 1 2 3 4 5 Punctual 1 2 3 4 5 Results 1 2 3 4 5 13–4 What Do I Measure?
- 5. Measurement Example • Measurement can be illustrated by thinking about the way instructors assign students’ grades A — Represents excellent performance B — Represents good performance C — Represents average performance D — Represents poor performance F — Represents failing performance • A student can be assigned a grade corresponding to a percentage performance scale. 90 -100 percent — Represents a perfect score. A Grade 80 – 89 percent – Represents B Grade 70–79 percent — Represents differing degrees of passing performance, each number representing the proportion of correct work. C Grade 60–69 percent — Represents failing performance but still captures proportion of correct work. D Grade 13–5
- 6. 13–6 EXHIBIT 13.2 Are There Any Validity Issues with this Measurement?
- 7. • Concepts A generalized idea that represents something of meaning A researcher has to know what to measure before knowing how to measure something. The problem definition process should suggest the concepts that must be measured. Concepts can be concrete and abstract Concepts such as age, gender, education, and number of children are relatively concrete properties. Concepts such as loyalty, personality, channel power, trust, corporate culture, customer satisfaction, value, and so on are abstract and more difficult to both define and measure 13–7 What Do I Measure?
- 8. 13–8 Operational Definitions • Operationalization The process of identifying scales that correspond to variance in a concept involved in a research process. • Scales A scale provides a range of values that correspond to different characteristics or amounts of a characteristic exhibited in observing a concept. • Correspondence rules Indicate the way that a certain value on a scale corresponds to some true value of a concept. An example of a correspondence rule: “Assign the numbers 1 through 7 according to how much trust that you have in your sales representative. If the sales representative is perceived as completely untrustworthy, assign the numeral 1, if the sales rep is completely trustworthy, assign a 7.”
- 9. 13–9 Operational Definitions (cont’d) • Variable Anything that varies or changes from one instance to another; can exhibit differences in value, usually in magnitude or strength, or in direction. Capture different values of a concept. Consider the following hypothesis: H1: Experience is positively related to job performance. The hypothesis implies a relationship between two variables, experience and job performance. • Constructs Concepts measured with multiple variables. Sometimes, a single variable cannot capture a concept alone. Using multiple variables to measure one concept can often provide a more complete account of some concept than could any single variable.
- 10. 13–10 Levels of Scale Measurement • Nominal Nominal scales are used for labeling variables, without any quantitative value. “Nominal” scales could simply be called “labels.” Assigns a value to an object for identification or classification purposes. Most elementary level of measurement. • Ordinal---Rank-Order Ranking scales allowing things to be arranged based on how much of some concept they possible. Have nominal properties. Ordinal scales are typically measures of non-numeric concepts like satisfaction, happiness, discomfort, etc.
- 11. 13–11 Levels of Scale Measurement (cont’d) • Interval Capture information about differences in quantities of a concept. Have both nominal and ordinal properties. Variables that have familiar, constant, and computable differences are classified using the Interval scale. • Ratio Highest form of measurement. Have all the properties of interval scales with the additional attribute of representing absolute quantities. Examples of variables which are ratio scaled include weights, lengths and times
- 12. 13–12 EXHIBIT 13.4 Nominal, Ordinal, Interval, and Ratio Scales Provide Different Information
- 15. Interval Scale Example • What is your family income? $0 to 10,000 $10,000 to 20,000 $20,000 to 30,000 More than $30,000 • Heat measured in degrees centigrade. 13–15
- 17. 13–17 EXHIBIT 13.5 Facts About the Four Levels of Scales
- 18. 13–18 Mathematical and Statistical Analysis of Scales • Discrete Measures Measures that can take on only one of a finite number of values. Discrete variables represent counts (e.g. the number of objects in a collection) • Continuous Measures Measures that reflect the intensity of a concept by assigning values that can take on any value along some scale range. Continuous variables represent measurable amounts (e.g. water volume or weight)
- 19. 13–19 Index Measures • Attributes Single characteristics or fundamental features that pertain to an object, person, or issue. • Index Measures Assign a value based on how much of the concept being measured is associated with an observation. Indexes often are formed by putting several variables together. Example of Socioeconomic status • Composite Measures Assign a value to an observation based on a mathematical derivation of multiple variables.
- 20. 13–20 Computing Scale Values • Summated Scale A scale created by simply summing (adding together) the response to each item making up the composite measure. • Reverse Coding Means that the value assigned for a response is treated oppositely from the other items.
- 21. 13–21 EXHIBIT 13.6 Computing a Composite Scale
- 22. 13–22 Three Criteria for Good Measurement Sensitivity Reliability Validity Good Measurement
- 23. 13–23 Reliability • Reliability The degree to which measures are free from random error and therefore yield consistent results. An indicator of a measure’s internal consistency. • Internal Consistency Represents a measure’s homogeneity or the extent to which each indicator of a concept converges on some common meaning. Measured by correlating scores on subsets of items making up a scale.
- 24. 13–24 Internal Consistency • Split-half Method Assessing internal consistency by checking the results of one-half of a set of scaled items against the results from the other half. • Coefficient alpha (α) The most commonly applied estimate of a multiple item scale’s reliability. Represents the average of all possible split-half reliabilities for a construct.
- 25. 13–25 Test-Retest Reliability • Test-retest Method Administering the same scale or measure to the same respondents at two separate points in time to test for stability. Represents a measure’s repeatability. • Problems: The pre-measure, or first measure, may sensitize the respondents and subsequently influence the results of the second measure. Time effects that produce changes in attitude or other maturation of the subjects.
- 26. 13–26 Validity • Validity The accuracy of a measure or the extent to which a score truthfully represents a concept. Does a scale measure what was intended to be measured? • Establishing Validity: Is there a consensus that the scale measures what it is supposed to measure? Does the measure correlate with other measures of the same concept? Does the behavior expected from the measure predict actual observed behavior?
- 27. 13–27 Validity (cont’d) • Face Validity A scale’s content logically appears to reflect what was intended to be measured. • Content Validity The degree that a measure covers the breadth of the domain of interest. • Criterion Validity The ability of a measure to correlate with other standard measures of similar constructs or established criteria. • Construct Validity Exists when a measure reliably measures and truthfully represents a unique concept.
- 28. 13–28 Validity (cont’d) • Convergent Validity Another way of expressing internal consistency; highly reliable scales contain convergent validity. • Discriminant Validity Represents how unique or distinct is a measure; a scale should not correlate too highly with a measure of a different construct.
- 29. 13–29 EXHIBIT 13.7 Reliability and Validity on Target
- 30. 13–30 Sensitivity • Sensitivity A measurement instrument’s ability to accurately measure variability in stimuli or responses. Generally increased by adding more response points or adding scale items.