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Introduction to Measurement Theory Measurement Theory Liu Xiaoling The Department of Psychology ECNU

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1 Introduction to Measurement Theory Measurement Theory Liu Xiaoling The Department of Psychology ECNU

2 Chapter 5 Reliability §1 Theory of Reliability  Interpretation of Reliability Reliability refers to the degree of consistency or reproducibility of measurements (or test scores). Reliability refers to the degree of consistency or reproducibility of measurements (or test scores).

3 Qualified Reliability Coefficient for Types of Tests for Types of Tests Ability or aptitude test, achievement test.90 and above.90 and above Personality, interests, value, attitude test.80 and above.80 and above

4 EXAMPLES  Stanford-Binet Fifth Edition: full-scale IQ (23 age ranges), ; test-retest reliability coefficients for verbal and nonverbal subtests, from the high.7’s to the low.9’s.  WISC-IV: split-half reliabilities for full scale IQ,.97  WAIS-III: average split-half reliability for full scale IQ is.98;.97 for verbal IQ;.94 for performance IQ  Thurstone’s Attitude Scale:  Rosenberg’s Self-Esteem Scale(1965): α( ); test –retest,.85

5  Errors— Inconsistent and inaccurate Effect Error Refers to the inconsistent and in accurate effects caused by the variable factors which are unrelated to the objective. Refers to the inconsistent and in accurate effects caused by the variable factors which are unrelated to the objective. Three Types: Random Systematic Sampling Random Systematic Sampling

6 Random Error An error due to chance alone, randomly distributed around the objective. Random errors reduce both the Random errors reduce both the consistency and the accuracy of the consistency and the accuracy of the test scores. test scores.

7 Systematic Error An error in data that is regular and repeatable due to improper collection or statistical treatment of the data. Systematic errors do not result in Systematic errors do not result in inconsistent measurement, but cause inconsistent measurement, but cause inaccuracy. inaccuracy.

8 Sampling Error Deviations of the summary values yielded by samples, form the values yielded by entire population.

9  Classical True Score Theory Assumptions:  One Formula X=T+E X=T+E X, an individual’s observed score E, random error score (error of measurement) T, the individual’s true score Founders: Charles Spearman (1904,1907,1913) J. P. Guilford (1936 )

10 CONCEPTION True score CTT assumes that each person has a true score that would be obtained if there were no errors in measurement. CTT assumes that each person has a true score that would be obtained if there were no errors in measurement. INTERPRETATION: INTERPRETATION: The average of all the observed scores obtained over an infinite number of repeated things with the same test. The average of all the observed scores obtained over an infinite number of repeated things with the same test.

11 TABLE 5.1 One Measure Data Observed Score True Score Error Error

12  Three Principles 1. The mean of the error scores for a population of examinees is zero. 1. The mean of the error scores for a population of examinees is zero. 2. The correlation between true and error scores for a population of examinees is zero. 2. The correlation between true and error scores for a population of examinees is zero. 3. The correlation between error scores from two independent testing is zero. 3. The correlation between error scores from two independent testing is zero.

13 Reliability Coefficient Reliability coefficient is the ratio of true score variance to observed score variance. Reliability coefficient can be defined as the correlation between scores on parallel test forms. Mathematical Definition: (5.1)

14 and As s e increases, r tt decrease if S t won’t vary. (5.2)

15 §2 Sources of Random Errors  Sources from Tests  Sources from Tests Administration and Scoring  Sources from Examinees

16  Sources from Tests Item sampling is lack of representativeness. Item sampling is lack of representativeness. Item format is improper. Item format is improper. Item difficulty is too high or too low. Item difficulty is too high or too low. Meaning of sentence is not clear. Meaning of sentence is not clear. Limit of test time is too short. Limit of test time is too short.

17  Sources from Tests Administration and Scoring and Scoring Test Conditions is negtive. Test Conditions is negtive. Examiner affects examinees’ performance. Examiner affects examinees’ performance. Unexpected disturbances occur. Unexpected disturbances occur. Scoring isn’t objective; counting is inaccurate. Scoring isn’t objective; counting is inaccurate.

18  Sources from examinees Motive for Test Motive for Test Negative Emotions ( e.g., anxiety) Negative Emotions ( e.g., anxiety) Health Health Learning, Development and Education Learning, Development and Education Experience in Test Experience in Test

19 §3 Estimates Reliability Coefficient Test-retest Reliability (Coefficient of Stability) Stability) Alternate-Forms Reliability (Coefficient of Equivalence) Equivalence) Coefficients of Internal Consistency Scorer reliability (Inter-rater Consistency)

20  Test-retest Reliability Also called Coefficient of Stability, which refers to the correlation between test scores obtained by administering the same form of a test on two separate occasions to the same examinee group. Also called Coefficient of Stability, which refers to the correlation between test scores obtained by administering the same form of a test on two separate occasions to the same examinee group. TEST RETEST TEST RETEST INTERVAL THE SAME examinee

21 REVIEW CORRELATION Figure 5.1 Scatter Plots for Two Variates

22 Formula for estimating reliability (5.3), test score, retest score, sample size Pearson product moment correlation coefficient

23 Application Example Test Testscore examinees examinees An subjective wellbeing scale administered to 10 high school students and half a year later they were tested the same scale again. Estimate the reliability of the scale. Table 5.2

24 Answer: Computing statistics

25 Transform of formula 5.3 (5.4) (5.4), mean of first test scores, mean of retest scores, standard deviation of first test scores, SD of retest scores

26 Quality of test-retest reliability:  Estimates the consistence of tests across time interval.  Sources of errors: Stability of the trait measured Stability of the trait measured Individual differences on development, education, learning, training, memory, etc.. Individual differences on development, education, learning, training, memory, etc.. Unexpected disturbances during test administration. Unexpected disturbances during test administration.

27  Alternate-Forms Reliability also called equivalent/ parallel forms reliability, which refers to the correlation between the test scores obtained by separately administering the alternate or equivalent forms of the test to the same examinees on one occasions. also called equivalent/ parallel forms reliability, which refers to the correlation between the test scores obtained by separately administering the alternate or equivalent forms of the test to the same examinees on one occasions. FORM Ⅰ FORM Ⅱ THE SAME examinee IMMEDIATE

28 ApplicationExample Two alternate forms of a creative ability test administered ten students in seventh grade one morning. Table 5.3 shows the test result. Estimate the reliability of this test. Table 5.3 Form of test examinees examinees

29 ANSWER: If use formula 5.4, then

30 Exercise1 Use formula 5.3 and 5.4 independently to estimate the reliability coefficient for the data in the following table. Use formula 5.3 and 5.4 independently to estimate the reliability coefficient for the data in the following table. Test Test Examinees Examinees AB

31 How to eliminate the effect of order of forms administered? How to eliminate the effect of order of forms administered?Method: First, divide one group of examinees into two parallel groups; First, divide one group of examinees into two parallel groups; Second, group one receives form Ⅰ of the test, and group two receives form Ⅱ ; Second, group one receives form Ⅰ of the test, and group two receives form Ⅱ ; Third, after a short interval, group one receives form Ⅰ, and group two receives form Ⅱ ; Third, after a short interval, group one receives form Ⅰ, and group two receives form Ⅱ ; Compute the correlation between all the examinees’ scores on two forms of the test. Compute the correlation between all the examinees’ scores on two forms of the test.

32 Sources of Error  Whether the two forms of test are parallel or equivalent, such as the consistence on content sampling, item format, item quantity, item difficulty, SD and means of the two forms.  Fluctuations in the individual examinee’s mind, in- cluding emotions, test motivation, health, etc..  Other unexpected disturbance.

33 Coefficient of Stability and Equivalence the correlation between the two group observed scores, when the two alternate test forms are administered on two separate occasions to the same examinees. the correlation between the two group observed scores, when the two alternate test forms are administered on two separate occasions to the same examinees. FORM Ⅰ FORM Ⅱ FORM Ⅰ FORM Ⅱ INTERVAL SAME EXAMINEES

34  Coefficients of Internal Consistency When examinees perform consistently across items within a test, the test is said to have item homogeneity. When examinees perform consistently across items within a test, the test is said to have item homogeneity. Internal consistency coefficient is an index of both item content homogeneity and item quality. Internal consistency coefficient is an index of both item content homogeneity and item quality.

35 Quality: One administration of a single form of test One administration of a single form of test Error sources: C ontent sampling C ontent sampling Fluctuations in the individual examinee’s state, including emotions, test motivation, health, etc.. Fluctuations in the individual examinee’s state, including emotions, test motivation, health, etc..

36 Split-Half Reliability Split-Half Reliability To get the split –half reliability, the test developer administers the test to a group of examinees; To get the split –half reliability, the test developer administers the test to a group of examinees; then divides the items in to two subtest, each half the length of the original test; then divides the items in to two subtest, each half the length of the original test; computes the correlation of the two halves of the test. computes the correlation of the two halves of the test. Procedures

37 Methods to divide the test into two parallel halves: two parallel halves: 1. Assign all odd-number items to half 1 and all even- number items to half Rank order the items in terms of their difficulty levels based on the responses of the examinees; then apply the method Randomly assign items to the two halves. 4. Assign items to half-test forms as that the forms are “matched ” in content.

38 Table 5.4 Illustrative Data for Split-half Reliability Estimation Examine e Item Half 1 Half X o Xe Total score X t p i p i q i St 2 =6.0

39 Employing formula 5.3 to compute r hh Attention: This r hh actually give the reliability of only a half-test. That is, it underestimates the reliability half-test. That is, it underestimates the reliability coefficient for the full-length test. coefficient for the full-length test.

40 Employ the Spearman-Brown formula to Employ the Spearman-Brown formula to correct r hh (5.5) (5.5)

41

42 Spearman-Brown general formula (5.6) (5.6) is the estimated coefficient is the estimated coefficient is the obtained coefficient is the obtained coefficient is the number of times the test is lengthened or shortened is the number of times the test is lengthened or shortened

43 Kuder-Richardson Reliability (Kuder & Kuder-Richardson Reliability (Kuder & Richardson,1 937) Richardson,1 937) Kuder-Richardson formula 20 (KR20) Kuder-Richardson formula 20 (KR20) ( 5.7) ( 5.7), the number of items, the total test variance,, the number of items, the total test variance,, the proportion of the examinees who pass each, the proportion of the examinees who pass each item item, the proportion of the examinees who do not pass, the proportion of the examinees who do not pass each item each item Dichotomously Scored Items

44 Employ the data in table 5.3,

45 Coefficient-Alpha ( ) (Cronbach,1951) Coefficient-Alpha ( ) (Cronbach,1951) (5.8 ) (5.8 ), the total test variance, the total test variance, the variance of item i, the variance of item i

46 Exercise 2 Suppose that examinees have been tested on four essay items in which possible scores range form 0 to 10 points, and,, Suppose that examinees have been tested on four essay items in which possible scores range form 0 to 10 points, and,,,. If total score variance is 100, then estimate the reliability of the test.,. If total score variance is 100, then estimate the reliability of the test.

47  Scorer reliability (Inter-rater Consistency) When a sample of test items are independently scored by two or more scorers or raters, each examinee should have several test scores. So there is a need to measure consistency of the scores over different scorers. When a sample of test items are independently scored by two or more scorers or raters, each examinee should have several test scores. So there is a need to measure consistency of the scores over different scorers.

48 Methods 1 The correlation between the two set of scores over two scorers (Pearson correlation; Spearman rank correlation ) 2 Kendall coefficient of concordance

49 Kendall coefficient of concordance (5.9) (5.9) K, the number of scorers, N , the number of examinees R i, the sum of ranks for each examinee over all scorers

50 examinee examinee rater Table 5.5 Scores of 6 Essays for 6 Examinees Employ formula 5.9, compute the scorer correlation. Key:.95

51 Type of Reliability Coefficient Error Variance Test -retest Alternate- Form Stability and Equivalence Coefficient Split -Half KR20 and αCoefficient Scorer Time sampling Content sampling Time and content sampling Content sampling Content sampling and content heterogeneity Inter-scorer differences Summing up Table 5.6 Sources of Error Variance in Relation to Reliability Coefficients

52 §4 Factors That Affect Reliability Coefficients Group Homogeneity Test Length Test difficulty

53  Group Homogeneity The magnitude of reliability coefficient depends on variation among individuals on both their ture scores and error scores. The magnitude of reliability coefficient depends on variation among individuals on both their ture scores and error scores. The score range is restricted, consequently, the true score variance is restricted, then the reliability coefficient is low. The score range is restricted, consequently, the true score variance is restricted, then the reliability coefficient is low.

54 Thus, the homogeneity of the examinee group Thus, the homogeneity of the examinee group is an important consideration in test development and test selection. Figure 5.2 Scatter Plots for Two Variates

55 Predicting how reliability is altered when sample variance is altered (5.10) (5.10), the predicted reliability estimate for new sample, the predicted reliability estimate for new sample, the variance of the new sample, the variance of the new sample, the variance of the original sample, the variance of the original sample, the reliability estimate for the original sample, the reliability estimate for the original sample

56 Exercise 3 Suppose one memory test have been administered to the all middle school students in one city, and the standard deviations of test score is 20, reliability coefficient is.90. If we also obtain 10, the standard deviation of test score for the students in grade two, please to predict the reliability coefficient for the students in grade two. Suppose one memory test have been administered to the all middle school students in one city, and the standard deviations of test score is 20, reliability coefficient is.90. If we also obtain 10, the standard deviation of test score for the students in grade two, please to predict the reliability coefficient for the students in grade two.

57  Test Length Which test seems more reliable? Which test seems more reliable? Test A 1+1= Test B 1+1= 2+2= 3+1= 4+2= 3+2= 5+3= 4+4= 1+6= 3+2= 5+3= 4+4= 1+6= 2+8= 4+5= = 2+8= 4+5= = Conclusion: reliability is higher for the test with more items (all based on the same content).

58 Using the Transform of Spearman-Brown General Formula to Determine the Length of the Test Using the Transform of Spearman-Brown General Formula to Determine the Length of the Test (5.11) (5.11)

59 Exercise 4 O ne language test has 10 items, and reliability coefficient is To make it’s reliability higher to.80, how many items the test developer should add into the test? O ne language test has 10 items, and reliability coefficient is To make it’s reliability higher to.80, how many items the test developer should add into the test?

60  Test Difficulty When a test is too hard or too easy for a group of examinees, restriction of score range, and the reliability coefficient is likely to be the result. When a test is too hard or too easy for a group of examinees, restriction of score range, and the reliability coefficient is likely to be the result.

61 §5 Standard Error of Measurement  Interpretation Theoretically, each examinee ‘s personal distribution of possible observed scores around the examinee’s true score has a standard deviation. When these individual error standard deviation are averaged for the group, the result is the standard error of measurement, and is denoted as. Theoretically, each examinee ‘s personal distribution of possible observed scores around the examinee’s true score has a standard deviation. When these individual error standard deviation are averaged for the group, the result is the standard error of measurement, and is denoted as.

62 Figure 5.3 Approximately Normal Distribution of Observed Scores for Repeated Testing of One Examinee (Form Introduction to Measurement Theory, M. J. Allen, & W. M. Yen, p89, 2002)

63 Figure 5.4 Hypothetical Illustration of different Examinees’ Distributions of Observed Scores Around Their True Score

64 Computation Formula (5.12) (5.12)

65  Use to Estimate one Examinee’s True Score Create a confidence interval around the examinee’s observed score. Create a confidence interval around the examinee’s observed score.

66 Example Known that the standard deviation of an intelligence scale is 15, r tt Known that the standard deviation of an intelligence scale is 15, r tt is.95. If one examinee’s IQ is 120, then create confidence interval for his/her true score. Answer: Then,


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