T4 measurement and scaling


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T4 measurement and scaling

  1. 1. Measurement and Scaling By Rama Krishna Kompella
  2. 2. Learning Objectives <ul><li>Understand the role of measurement in marketing research </li></ul><ul><li>Explain the four basic levels of scales </li></ul><ul><li>Describe scale development and its importance gathering primary data </li></ul><ul><li>Discuss comparative and noncomparative scales </li></ul>
  3. 3. Basic Measurement Issues <ul><li>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. </li></ul><ul><li>We do not measure specific objects, persons, etc., we measure attributes or features that define them. </li></ul><ul><li>Ex., What defines the person Brent Wren? What is a student’s level of education? How customer oriented is our company? </li></ul><ul><li>Overriding Goal: To provide a valid and reliable description or enumeration of the person, objects, issue, etc. </li></ul>
  4. 4. Accuracy of Measurements <ul><li>Why do scores on a measurement scale differ? </li></ul><ul><ul><li>A true difference in the characteristic being measured. </li></ul></ul><ul><ul><li>Short-term personal factors (e.g., moods, time constraints) </li></ul></ul><ul><ul><li>Situational factors (e.g., surroundings) </li></ul></ul><ul><ul><li>Variations in method of administering survey. </li></ul></ul><ul><ul><li>Sampling of items included in the questionnaire. </li></ul></ul><ul><ul><li>Lack of clarity in the measurement instrument. </li></ul></ul><ul><ul><li>Mechanical or instrument factors causing completion errors. </li></ul></ul>
  5. 5. Measurement Process <ul><li>Define concepts to be measured </li></ul><ul><li>Define attributes of the concepts </li></ul><ul><li>Select scale of measurement (data type) </li></ul><ul><li>Generate Items/Questions </li></ul><ul><ul><li>Wording </li></ul></ul><ul><ul><li>Response format </li></ul></ul><ul><li>Layout and design questionnaire </li></ul><ul><li>Pretest and refine </li></ul>
  6. 6. Some Key Concepts <ul><li>Measurement </li></ul><ul><ul><li>Assigning numbers or other symbols to characteristics of objects being measured, according to predetermined rules. </li></ul></ul><ul><li>Concept (or Construct) </li></ul><ul><ul><li>A generalized idea about a class of objects, attributes, occurrences, or processes. </li></ul></ul><ul><ul><ul><li>Relatively concrete constructs </li></ul></ul></ul><ul><ul><ul><ul><li>Age, gender, number of children, education, income </li></ul></ul></ul></ul><ul><ul><ul><li>Relatively abstract constructs </li></ul></ul></ul><ul><ul><ul><ul><li>Brand loyalty, personality, channel power, satisfaction </li></ul></ul></ul></ul>
  7. 7. <ul><li>Scaling </li></ul><ul><ul><li>The generation of a continuum upon which measured objects are located. </li></ul></ul><ul><li>Scale </li></ul><ul><ul><li>A quantifying measure – a combination of items that is progressively arranged according to value or magnitude. </li></ul></ul><ul><ul><li>Purpose is to quantitatively represent an item’s, person’s, or event’s place in the scaling continuum. </li></ul></ul>Some Key Concepts
  8. 8. Four Basic Scales of Measurement Nominal Scales Ordinal Scales Interval Scales Ratio Scales
  9. 9. Primary Scales of Measurement Bob Gene Sam Scale Nominal Symbols Assigned to Runners Ordinal Rank Order of Winners Interval Performance Rating on a 0 to 10 Scale Ratio Time to Finish, in Seconds Finish Finish 3 7 9 15.2 14.1 13.4 3 rd place 2 nd place 1 st place
  10. 10. Primary Scales of Measurement Nominal Scale <ul><li>The numbers serve only as labels or tags for identifying and classifying objects. </li></ul><ul><li>When used for identification, there is a strict one-to-one correspondence between the numbers and the objects. </li></ul><ul><li>The numbers do not reflect the amount of the characteristic possessed by the objects. </li></ul><ul><li>The only permissible operation on the numbers in a nominal scale is counting. </li></ul><ul><li>Only a limited number of statistics, all of which are based on frequency counts, are permissible, e.g., percentages, and mode. </li></ul>
  11. 11. Primary Scales of Measurement Ordinal Scale <ul><li>A ranking scale in which numbers are assigned to objects to indicate the relative extent to which the objects possess some characteristic. </li></ul><ul><li>Can determine whether an object has more or less of a characteristic than some other object, but not how much more or less. </li></ul><ul><li>Any series of numbers can be assigned that preserves the ordered relationships between the objects. </li></ul><ul><li>In addition to the counting operation allowable for nominal scale data, ordinal scales permit the use of statistics based on centiles, e.g., percentile, quartile, median. </li></ul>
  12. 12. Primary Scales of Measurement Interval Scale <ul><li>Numerically equal distances on the scale represent equal values in the characteristic being measured. </li></ul><ul><li>It permits comparison of the differences between objects. For example, the difference between 1 and 2 is the same as between 3 and 4. The difference between 1 and 9 (i.e., 8) is twice as large as the difference between 2 and 4 (i.e., 2) or 6 and 8 (2). </li></ul><ul><li>The location of the zero point is not fixed. Both the zero point and the units of measurem. are arbitrary. </li></ul><ul><li>It is NOT meaningful to take ratios of scale values </li></ul><ul><li>It IS meaningful to take ratios of their differences. </li></ul><ul><li>Statistical techniques that may be used include all of those that can be applied to nominal and ordinal data, and in addition the arithmetic mean, standard deviation, correlation, and other common statistics. </li></ul><ul><li>But NOT: geometric or harmonic mean, nor CV = S/X </li></ul>
  13. 13. Primary Scales of Measurement Ratio Scale <ul><li>Possesses all the properties of the nominal, ordinal, and interval scales. </li></ul><ul><li>It has an absolute zero point. Examples: height, weight, age, money, sales, costs, market share, number of customers, the rate of return. </li></ul><ul><li>It is meaningful to compute ratios of scale values. </li></ul><ul><li>For example, not only is the difference between 2 and 5 the same as the difference between 14 and 17, but also 14 is seven times as large as 2 in an absolute sense. </li></ul><ul><li>All statistical techniques can be applied to ratio data. </li></ul>
  14. 14. Primary Scales of Measurement
  15. 15. Generate Items <ul><li>Items are basically questions </li></ul><ul><li>Need to ensure that enough questions are asked to generate information necessary to address research problems. </li></ul><ul><li>Likely will have a mix of question types and scales of measurement </li></ul><ul><li>Multi-item, Composite or Index Measures </li></ul><ul><ul><li>A measurement scale containing multiple questions addressing same construct or attribute </li></ul></ul>
  16. 16. A Classification of Scaling Techniques Likert Semantic Differential Stapel Scaling Techniques Noncomparative Scales Comparative Scales Constant Sum Paired Comparison Rank Order Q-Sort and Other Procedures Continuous Rating Scales Itemized Rating Scales
  17. 17. <ul><li>Respondent is presented with two objects at a time </li></ul><ul><li>Then asked to select one object in the pair according to some criterion </li></ul><ul><li>Data obtained are ordinal in nature </li></ul><ul><ul><li>Arranged or ranked in order of magnitude </li></ul></ul><ul><li>Easy to do if only a few items are compared. </li></ul><ul><li>If number of comparisons is too large, respondents may become fatigued and no longer carefully discriminate among them. </li></ul>Paired Comparison Scaling
  18. 18. Paired Comparison Scaling: Example For each pair of professors, please indicate the professor from whom you prefer to take classes with a 1. Cunningham Day Parker Thomas Cunningham 0 0 0 Day 1 1 0 Parker 1 0 0 Thomas 1 1 1 0 # of times preferred 3 1 2 0
  19. 19. <ul><li>Respondents are presented with several objects simultaneously </li></ul><ul><li>Then asked to order or rank them according to some criterion. </li></ul><ul><li>Data obtained are ordinal in nature </li></ul><ul><ul><li>Arranged or ranked in order of magnitude </li></ul></ul><ul><li>Commonly used to measure preferences among brands and brand attributes </li></ul>Rank Order Scaling
  20. 20. Rank Order Scaling Please rank the instructors listed below in order of preference. For the instructor you prefer the most, assign a “1”, assign a “2” to the instructor you prefer the 2 nd most, assign a “3” to the instructor that you prefer 3 rd most, and assign a “4” to the instructor that you prefer the least. Instructor Ranking Cunningham 1 Day 3 Parker 2 Thomas 4
  21. 21. <ul><li>Respondents are asked to allocate a constant sum of units among a set of stimulus objects with respect to some criterion </li></ul><ul><li>Units allocated represent the importance attached to the objects. </li></ul><ul><li>Data obtained are interval in nature </li></ul><ul><li>Allows for fine discrimination among alternatives </li></ul>Constant Sum Scaling
  22. 22. Constant Sum Scaling Listed below are 4 marketing professors, as well as 3 aspects that students typically find important. For each aspect, please assign a number that reflects how well you believe each instructor performs on the aspect. Higher numbers represent higher scores. The total of all the instructors’ scores on an aspect should equal 100. Instructor Availability Fairness Easy Tests Cunningham 30 35 25 Day 30 25 25 Parker 25 25 25 Thomas 15 15 25 Sum Total 100 100 100
  23. 23. Graphic Rating Scale
  24. 24. A Classification of Scaling Techniques Likert Semantic Differential Stapel Scaling Techniques Noncomparative Scales Comparative Scales Paired Comparison Rank Order Constant Sum Q-Sort and Other Procedures Continuous Rating Scales Itemized Rating Scales
  25. 25. Continuous Rating Scale Example Very Poor Very Good 0 10 20 30 40 50 60 70 80 90 100 X
  26. 26. Likert Scale A likert scale is an ordinal scale format that asks respondents to indicate the extent to which they agree or disagree with a series of mental or behavioral belief statements about a given object
  27. 27. Likert Scale Example
  28. 28. Semantic Differential Scale A semantic differential scale is unique bipolar ordinal scale format that captures a person’s attitudes and/or feelings about a given object
  29. 29. Semantic Differential Scale Format
  30. 30. Behavioral Intention Scale A behavioral intention scale is a special type of rating scale designed to capture the likelihood that people will demonstrate some type of predictable behavior intent toward purchasing an object or service in a future time frame
  31. 31. Shopping Intention Scale
  32. 32. Figure 10.6 Scale Evaluation Scale Evaluation Scale Evaluation Reliability Validity Test-Retest Internal Consistency Alternative Forms Construct Criterion Content Convergent Validity Discriminant Validity Nomological Validity
  33. 33. Reliability <ul><li>Extent to which a scale produces consistent results </li></ul><ul><li>Test-retest Reliability </li></ul><ul><ul><li>Respondents are administered scales at 2 different times under nearly equivalent conditions </li></ul></ul><ul><li>Alternative-form Reliability </li></ul><ul><ul><li>2 equivalent forms of a scale are constructed, then tested with the same respondents at 2 different times </li></ul></ul>
  34. 34. Reliability <ul><li>Internal Consistency Reliability </li></ul><ul><ul><li>The consistency with which each item represents the construct of interest </li></ul></ul><ul><ul><li>Used to assess the reliability of a summated scale </li></ul></ul><ul><ul><li>Split-half Reliability </li></ul></ul><ul><ul><ul><li>Items constituting the scale divided into 2 halves, and resulting half scores are correlated </li></ul></ul></ul><ul><ul><li>Coefficient alpha (most common test of reliability) </li></ul></ul><ul><ul><ul><li>Average of all possible split-half coefficients resulting from different splittings of the scale items </li></ul></ul></ul>
  35. 35. Validity <ul><li>Extent to which true differences among the objects are reflected on the characteristic being measured </li></ul><ul><li>Content Validity </li></ul><ul><ul><li>A.k.a., face validity </li></ul></ul><ul><ul><li>Subjective, but systematic evaluation of the representativeness of the content of a scale for the measuring task at hand </li></ul></ul><ul><li>Criterion Validity </li></ul><ul><ul><li>Examines whether measurement scale performs as expected in relation to other variables selected as meaningful criteria </li></ul></ul><ul><ul><li>I.e., predicted and actual behavior should be similar </li></ul></ul>
  36. 36. Construct Validity <ul><li>Addresses the question of what construct or characteristic the scale is actually measuring </li></ul><ul><li>Convergent Validity </li></ul><ul><ul><li>Extent to which scale correlates positively with other measures of the same construct </li></ul></ul><ul><li>Discriminant Validity </li></ul><ul><ul><li>Extent to which a measure does not correlate with other constructs from which it is supposed to differ </li></ul></ul><ul><li>Nomological Validity </li></ul><ul><ul><li>Extent to which scale correlates in theoretically predicted ways with measures of different but related constructs </li></ul></ul>
  37. 37. Relationship Between Reliability and Validity <ul><li>A scale can be reliable, but not valid </li></ul><ul><li>In order for a scale to valid, it must also be reliable. </li></ul><ul><li>In other words, </li></ul><ul><ul><li>Reliability is a necessary but insufficient condition for Validity. </li></ul></ul>
  38. 38. Reliability and Validity on Target Old Rifle New Rifle New Rifle Sunglare Low Reliability High Reliability Reliable but Not Valid (Target A) (Target B) (Target C)
  39. 39. Q & As