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Chapter11 Measurement

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Chapter11 Measurement

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  1. 授課教授 : 洪新原教授 李彥杰 602556001 鄭玲潔602556027 周敬堯602556025 Chapter11 Measurement

  2. The Nature of Measurement • Measurement in research consists of assigning numbers to empirical events, objects or properties, or activities in compliance with a set of rules. • This slide illustrates the three-part process of measurement. A mapping rule is a scheme for assigning numbers to aspects of an empirical event.

  3. Empirical Researchers use an empirical approach to describle,explain,and make predictions by relying on information gained through observation.

  4. Characteristics of Measurement 樣本元素 實證觀察 映射規則 符號

  5. measurement – • of assigning numbers to empirical events in compliance with a set of rules

  6. An operational definition defines a variable in terms of specific measurement and testing criteria

  7. What is measured ? The concepts of ordinary experience • Physical properties • Psychological properties • Social properties P273Exhibit11-2

  8. Measurement Scales Nominal Classification Classification Ordinal Order interval Classification Distance Order Ratio Classification Distance Order Natural Origin Exhibit11-3

  9. 調查問題 10

  10. Nominal Scales 名目尺度 • Just Labels , not have quantitative value • Nominal scales are the least powerful of the four data types . • The number count of cases in each category (the frequency distribution) ,the researcher is retricted to the use of the mode as the measureof central tendency.

  11. The mode (眾數) • – the most frequently occurring value. • classify a set of properties into a set of equivalent classes. • Valuable • - The objective is to uncover relationships rather than secure precise measurements. • This type of scale is also widely used in survey and other research when data are classified by major subgroups of the population.

  12. Ordinal Scales • Include the characteristics of nominal scale plus an indication of oder. • Ordinal data require conformity to a logical postulate:if a is greater than b and b is greater than c,then a is greater than . • Ordinal data include attitude and preference scales. • The numbers used with ordinal scales have only a rank meaning,the appropriate measure of central tendency is the median. • Correlational analysis of ordinal data is restricted to various ordinal technique.

  13. Interval Scales • Have the power of nominal and ordinal data plus one additional strength- the concept of equality of interval. • When a scale is interval and the data are relatively symmetric with one model, you use the arithmetic mean as the measure of central tendency. • The standard deviation is the measure of dispersion. • The product-moment correlation,t-test,F-test,and other parametric tests are the stistical procedures of choice for interval data. • Use the median as the measure of central tendency and the interquartile range as the measure of dispersion.

  14. Ratio Scales • Incorporate all of the powers of the previous scales plus the provision for absolute zero or origin. • Ratio data represent the actual amounts of a variable. • Measures of physical dimensions such as weight,height…

  15. Sources of Measurement Differences • Much error is systematic(results from a bias), while the remainder is random(occurs erratically). • Four major error sources may contaminate the results: • The respondent • The situation • The measurer • The data collection instrment

  16. The respondent • Opinion differences that affect measurement come from relatively stable characteristics of respondent. • Typical of these are employee status, ethnic group membership, social class, and nearness to manufacturing facilities. • Respondent also suffer from temporary factors like fatigue, boredom.

  17. The situation • Any condition that places a strain on the interview of measurement session can have serious effects on the interviewer-respondent rapport.

  18. The Measurer • The interviewer can distort response by rewording, paraphrasing, or reordering question. • In the data analysis stage, incorrect coding, careless tabulation, and faulty statistical calculation may introduce further errors.

  19. The Instrument • A defective instrument can cause distortion in two major ways • It can be too confusing and ambiguous. • Poor selection from the universe of content items.

  20. The Characteristics of Good Measurement • What are the characteristics of a good measurement tool? A tool should be an accurate indicator of what one needs to measure. It should be easy and efficient to use. • There are three major criteria for evaluating a measurement tool: • Validity is the extent to which a test measures what we actually wish to measure. • Reliability refers to the accuracy and precision of a measurement procedure. • Practicality is concerned with a wide range of factors of economy, convenience, and interpretability.

  21. Validity • The text features two major forms: • External validity • Internal validity • There are three major forms of validity: • Content • Construct • Criterion

  22. Validity

  23. Validity Determinants Content Criterion Construct

  24. Content validity Content Criterion Construct

  25. Content validity • To evaluate content validity • one must first agree on what elements constitute adequate coverage. • To determine content validity • one may use one’s own judgment and the judgment of a panel of experts. • Content validity is primarily concerned with inferences about test construction rather than inferences about test scores

  26. Increasing Content Validity Content Literature Search Etc. Expert Interviews Question Database Group Interviews

  27. Criterion – related validity Content Criterion Construct

  28. two types of criterion validity: Criterion Concurrent predictive

  29. Judging Criterion Validity Relevance Criterion Freedom from bias Reliability Availability

  30. Construct validity Content Construct

  31. Increasing Construct ValidityConvergent / discriminant validity New measure of trust Known measure of trust Empathy Credibility

  32. Understanding Validity and Reliability

  33. Reliability

  34. Reliability Estimates Stability Internal Consistency Equivalence

  35. Reliability Stability Stability Internal Consistency Equivalence

  36. Reliability - Stability • Observation studies • Survey situation • Test-retest • can be used to assess stability. • Cause bias: • 1.Time delay between measurements • 2.Insufficient time between measurements • 3.Respondent’s discernment of a study’s disguised purpose • 4.Topic sensitivity

  37. Reliability - Equivalence Stability Internal Consistency Equivalence

  38. Reliability Internal Consistency Stability Internal Consistency Equivalence

  39. Practicality

  40. Practicality measurement requirements : process to be reliable and valid operational requirements : call for it to be practical. Economy Convenience Interpretability

  41. 1.A statement of the functions ; • 2. Detailed instructions for administration; • 3. Scoring keys and instructions; • 4. Norms for appropriate reference groups; • 5. Evidence of reliability; • 6. Evidence regarding the intercorrelations of subscores; • 7. Evidence regarding the relationship of the test to other measures; and • 8. Guides for test use. Interpretability