Chapter 9

1. Chapter 9 Carl McDaniel, Jr. Roger Gates Slides Prepared by Bruce R. Barringer University of Central Florida Understanding Measurement

2. Learning Objectives • To understand the concept of measurement. • To learn about the measurement process and how to develop a good measurement. • To understand the four levels of scales and their typical usage. • To become aware of the concepts of reliability and validity.

3. The Concept of Measurement Measurement is the process of assigning numbers or labels to objects, persons, states, or events in accordance with specific rules to represent quantities or qualities of attributes.

4. Rule Defined A rule is a guide, a method, or a command that tells a researcher what to do.

5. The Measurement Process research findings Which leads to utilizes the scales Develop a construct If the evaluation is satisfactory, the researcher Use the concept to Which is used to create Identify the concept of interest a constitutive definition evaluate the reliability and the validity of the scales measurement scales Which enables a researcher to develop an That require the researcher to operational definition Which enables a researcher to create

6. Step One: Identify the Concept of Interest • Measurement begins by identifying a concept of interest for study. • A concept is an abstract idea generalized from particular facts.

7. Step Two: Develop a Construct • Constructs are specific types of concepts that exist at higher levels of abstraction. • Constructs are invented for theoretical use. • The value of specific constructs depends on how useful they are in explaining, predicting, and controlling phenomena, just as the value of everyday concepts depends on how much they assist us in everyday affairs.

8. Steps Three and Four: Define the Concept Both Constitutively and OperationallySlide 1 of 2 • Constitutive • A constitutive (or theoretical or conceptual) definition defines a concept with other concepts and constructs, establishing boundaries for the construct under study; it states the central idea or concept under study.

9. Steps Three and Four: Define the Concept Both Constitutively and OperationallySlide 2 of 2 • Operational Definition • An operational definition defines which observable characteristics will be measured and the process for assigning a value to the concept. • In other words, an operational definition serves as a bridge between a theoretical concept and real-world events or factors.

10. Step Five: Develop a Measurement Scale • Scale • A scale is a set of symbols or numbers so constructed that the symbols or numbers can be assigned by a rule to the individuals (or their behaviors or attitudes) to whom the scale is applied.

11. Types of ScalesSlide 1 of 8 • Nominal Scale • Description • Uses numerals to identify objects, individuals, events, or groups. • Basic Empirical Operations • Determination of equality/inequality • Typical Usage • Classification (male/female; buyer/nonbuyer)

12. Types of ScalesSlide 2 of 8 • Nominal Scale (continued) • Typical Descriptive Statistics • Frequency Counts, percentages/modes • Example of Nominal Scale • Sex (1) Male (2) Female • Geographic Area (1) Urban (2) Rural (3) Suburban

13. Types of ScalesSlide 3 of 8 • Ordinal Scale • Description • In addition to identification, the numerals provide information about the relative amount of some characteristic posed by an event, object, etc. • Basic Empirical Operations • Determination of greater or less. • Typical Usage • Rankings/ratings

14. Types of ScalesSlide 4 of 8 • Ordinal Scale (continued) • Typical Descriptive Statistics • Median (mean and variance metric) • Example of Ordinal Scale: • Please rank the following fax machines from 1 to 5 with 1 being the most preferred and 5 the least preferred. • _____ Panasonic • _____ Toshiba • _____ Sharp • _____ Savin • _____ Ricoh

15. Types of ScalesSlide 5 of 8 • Interval Scale • Description • Possesses all the properties of nominal and ordinal scales plus the intervals between consecutive points are equal. • Basic Empirical Operations • Determination of equality of intervals. • Typical Usage • Preferred measure of complex concepts/constructs.

16. Types of ScalesSlide 6 of 8 • Interval Scale (continued) • Typical Descriptive Statistics • Mean/variance • Example of an Interval Scale • Thermometer

17. Types of ScalesSlide 7 of 8 • Ratio Scale • Description • Incorporates all the properties of nominal, ordinal, and interval scales plus it includes an absolute zero point. • Basic Empirical Operations • Determination of equality of ratios. • Typical Usage • When precision instruments are available.

18. Types of ScalesSlide 8 of 8 • Ratio Scale (continued) • Typical Descriptive Statistics • Mean. • Example of a Ratio Scale • Age, weight, height, population of the U.S., etc.

19. Step Six: Evaluate the Reliability and Validity of the Measures • Reliability • Is the degree to which measures are free from random error and, therefore, provide consistent data. • Validity • Validity addresses the issue of whether what we try to measure was actually measured.

20. Assessing the Reliability of a Measurement Instrument Test-Retest Reliability Use the same instrument a second time under nearly the same conditions as possible. Equivalent Form Reliability Use two instruments that are as similar as possible to measure the same object during the same time period. Internal Consistency Compare different samples of items being Reliability used to measure a phenomenon during the same time period.

21. Assessing the Validity of a Measurement InstrumentSlide 1 of 2 Face Validity Researchers judge the degree to which a measurement instrument seems to measure what it is supposed to. Content Validity The degree to which the instrument items represent the universe of the concept under study.

22. Assessing the Validity of a Measurement InstrumentSlide 1 of 2 Criterion-related Validity The degree to which a measurement instrument can predict a variable that is designed a criterion. A. Predictive Validity- The extent to which a future level of a criterion variable can be predicted by a current measurement on a scale. B. Concurrent Validity- The extent to which a criterion variable measured at the same point in time as the variable of interest can be predicted by the measurement instrument.

23. Assessing the Validity of a Measurement InstrumentSlide 2 of 2 Construct Validity The degree to which a measure confirms a hypothesis created from a theory based upon the concepts under study. A. Convergent validity - The degree of association among different measurement instruments that purport to measure the same concept. B. Discriminant Validity - The lack of association among constructs that are supposed to be different.

24. Illustrations of Possible Reliability and Validity Situations in Measurement Situation 1 Situation 2 Situation 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Neither reliable nor valid Highly reliable but not valid Highly reliable and valid

25. Summary of Key PointsSlide 1 of 3 • Measurement consists of using rules to assign numbers to objects in such a way as to represent quantities of attributes. • A measurement rule is a guide, a method, or command that tells the researcher what to do. • Accurate measurement requires rules that are both clear and specific.

26. Summary of Key PointsSlide 2 of 3 • The measurement process is as follows: identify the concept of interest, develop a construct, define the concept constitutively and operationally, develop a measurement scale, evaluate the reliability and validity of the scale, and then use the scale. • There are four basic levels of measurement: nominal, ordinal, interval, and ratio.

27. SummarySlide 3 of 3 • Measurement data consists of accurate information and errors. • Reliability is the degree to which measures are free from random error and therefore provide consistent data. • Validity refers to the notion of actually measuring what we are attempting to measure.