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Psyc 820 - MCQs > Psychometrics in Neuropsychological Assessment (Strauss, 2006) > Flashcards

Psychometrics in Neuropsychological Assessment (Strauss, 2006) Flashcards

1
Q

How do you calculate a z-score?

A

obtained score - sample mean/ sample SD

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2
Q

What is the mean and SD of a Z-score?

A 
Mean = 0
SD = 1
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3
Q

What is a Z-score?

A

A type of standard score

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4
Q

What does a Z-score quantify?

A

How many SDs a score is from the mean

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5
Q

What is a t-score?

A

Another linear transformation of a raw score

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6
Q

What is the mean and SD of a t-score?

A 
Mean = 50
SD = 10
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7
Q

Why do we use standard scores?

A

By virtue of conversion to a common metric, they facilitate the comparison of scores across measures

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8
Q

What must the distribution of the tests be for us to use standardized scores?

A

Approximately normal

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9
Q

What are two things that must be considered before comparing test scores?

A
  1. The reliability of the 2 measures

2. Their intercorrelation

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10
Q

How can you calculate the prevalence value from a z-score?

A
  1. Look up the corresponding estimated frequency (e.g., -4) in a z-score table
  2. Divide 1 by that value (e.g., .00003/1 = 31,560)

Thus, the estimated prevalence of -4 is 1 in 31,560

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11
Q

A test with a normal distribution in the general population may show extreme skew or other divergence from normality when administered to a population that differs considerably from the average individual. Give an example.

A

Vocab test being negatively skewed when administered to doctoral students in literature vs positively skewed when given to preschoolars who recently immigrated

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12
Q

When a new test is constructed, how can non-normality be corrected?

A

By examining the distribution of scores on the prototype test, adjusting test properties and resampling until a normal distribution is reached

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13
Q

What is another way of saying negatively skewed (in terms of testing)?

A

low ceiling

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14
Q

What is another way of saying positively skewed (in terms of testing)?

A

high ceiling

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15
Q

Will a large N correct for non-normality of an underlying population distribution?

A

No - a larger sample will only produce a more normal distribution if the underlying population distribution from which the sample was obtained is normal

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16
Q

What factors may lead to non-normal test score distributions?

A
  1. The existence of discrete subpopulations within the general population with differing abilities
  2. Ceiling or floor effects
  3. Treatment effects that change the location of means, medians and modes and affect variability and distribution shape
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17
Q

Small samples may yield non-normal distributions due to what?

A

Random sampling effects

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18
Q

What is a formal measure of asymmetry?

A

Skewness

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19
Q

What is the skew value of a true normal distribution?

A

0

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20
Q

What will have a skew value NEAR 0?

A

A non-normal but symmetric distribution

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21
Q

What do negative skew values indicate?

A

That the left tail of the distribution is heavier than the right

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22
Q

What does skewness tell us about the mean and median?

A

If there is skewness then the mean and median are not identical because the mean will not be at midpoint in rank

Z-scores will not accurately translate into sample percentile rank values

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23
Q

What increases as skew increases?

A

Error in mapping z-scores to sample percentile ranks

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24
Q

What kind of distributions often have significant skew? Give an example.

A

Truncated distributions often have significant skew

Truncated distributions often occur when range is restricted: e.g., reaction time

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25
Q

Floor and ceiling effects may be defined as what?

A

The presence of truncated tails in the context of limitations in range of item difficulty

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26
Q

What does a high floor mean?

A

All items difficult

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27
Q

What does a low ceiling mean?

A

All items easy

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28
Q

What does multimodality refer to?

A

The presence of more than one peak in a frequency distribution

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29
Q

Non-normality has major implications for interpreting and comparing standard scores - elaborate.

A

Standardized scores derived by linear transformation will not correspond to sample percentiles and the degree of divergence can be quite high

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30
Q

Normalizing transformations introduce error - when is it acceptable to normalize scores?

A

1) If they come from a large and representative sample

2) If any deviation from normality arises from defects in the test rather than characteristics of the sample

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31
Q

Normalizing transformations introduce error, what is the preferable way to handle non-normality in scores?

A

Preferable to adjust score distributions prior to normalization by modifying test content rather than statistically transforming non-normal scores into a normal distribution

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32
Q

Define reliability

A

The consistency of measurement of a given test and can be defined in several ways, including consistency within itself (internal consistency reliability) and consistency over time (test-retest reliability)

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33
Q

What do indices of reliability show?

A

The degree to which a test is free from measurement error

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34
Q

Internal consistency reliability

A

The tests reliability with itself

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35
Q

Reliability coefficients are influenced by what two things?

A
  1. Test characteristics

Sample characteristics

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36
Q

Reliability coefficients are influenced by test characteristics - list some examples of test characteristics

A

Length, item type, item homogeneity, influence of guessing

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37
Q

Reliability coefficients are influenced by sample characteristics - list some examples of sample characteristics

A

Sample size, range, variability

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38
Q

Test clarity is closely related to reliability. What is meant by test clarity?

A
  1. Clearly written
  2. Easily understood instructions
  3. Standardized administration conditions
  4. Exploring scoring rules that minimize subjectivity
    A process for training raters
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39
Q

What is internal reliability?

A

The extent to which items within a test measure the same cognitive domain or construct

A measure of the inter-correlation of items, internal reliability is an estimate of the correlation between randomly parallel test forms, and by extension, correlation between test scores and true scores.

40
Q

Describe and provide examples of the major sources of measurement error

A

Time sampling error- is associated with the fluctuation in test scores obtained from repeated testing of the same individual.

Content-Sampling Error- is the term used to label the error that results from selecting test items that inadequately cover the content area that the test is supposed to evaluate.

Also: Quality of test items, test length, test-taker variables, and lastly the test administration.

41
Q

Do longer or shorter tests yield higher reliability estimates

A

Longer

42
Q

What is split half reliability

A

Correlating two halves of items from the same test - a type of internal reliability

43
Q

What is another term for split half reliability?

A

Spearman-brown reliability coefficient

44
Q

What is the error variance associated with split-half reliability?

A

Content sampling

45
Q

What is the Kuder-Richardson reliability coefficient?

A

A type of internal reliability - used for yes/no items or heterogeneous tests where split half is necessary

46
Q

What is the error variance associated with Kuder-Richardson?

A

A type of internal reliability - used for yes/no items or heterogeneous tests where split half is necessary

47
Q

What is the coefficient alpha?

A

General estimate of reliability based on all the possible ways of splitting up test items - an internal reliability coefficient

48
Q

What are the 3 internal reliability coefficients?

A
  1. Split-half or Spearman-brown
  2. Coefficient alpha
    Kuder-Richardson
49
Q

What is the type of error variance associated with test-retest reliability?

A

Time sampling

50
Q

What are the advantages, in terms of reliability, of speed tests?

A
  1. Very high internal reliability estimates

Reliabilities can also be divided into specific time intervals

51
Q

What is another term for test-retest reliability?

A

Temporal stability

52
Q

What is test-retest reliability?

A

An estimate of the correlation between two test scores from the same test administered at 2 different times

53
Q

What are you looking for in test-retest reliability?

A

Little change over time - this shows that there are no differential effects of prior exposure

54
Q

What kind of tests will show lower test-retest reliability? What kind will show higher?

A

Tests measuring dynamic (changeable) abilities will show lower test-retest reliability than tests measuring more trait-like or stable abilities

55
Q

What kind of situational variables can impact an individual’s test score over time on the same test?

A

State, examiner state, examiner identity, environmental conditions

56
Q

What are 3 sources of bias in test-retest situations?

A
  1. Intervening variables (e.g., surgery)
  2. Practice effects
  3. Demographic considerations (Age, education etc.)
57
Q

What are two types of statistical error associated with test-retest reliability?

A

Measurement error and regression to the mean

58
Q

What is the type of coefficient associated with test-retest reliability?

A

stability coefficient

59
Q

What is the purpose alternate forms reliability?

A

It attempts to eliminate confounding effects of practice when a test has to be administered more than once

60
Q

Types of error associated with alternate forms reliability

A

Time sampling error and content sampling error

61
Q

Why do alternate forms not necessarily eliminate effects of prior exposure?

A

Because exposure to stimuli and procedures can introduce carry over effects too

(these effects are less for tests assessing acquired knowledge)

62
Q

What is inter-rater reliability?

A

Reliability of administration and scoring

63
Q

How do you evaluate inter-rater reliability?

A
  1. Percentage agreement
  2. Kappa
  3. Product-moment correlation
64
Q

What is Generalizability/G-theory?

A

Reliability is evaluated by decomposing test score variance into between- and within-group variance using the general linear model

65
Q

What is between groups variance considered to be an estimate of?

A

True score variance

66
Q

What is within group variance considered to be an estimate of?

A

Error variance

67
Q

What is the coefficient associated with G-theory?

A

Generalizability coefficient - the ratio of estimated true variance to the sum of the estimates of true variance and estimated error variance

68
Q

Does high reliability indicate high validity?

A

No

69
Q

Will reliability stay the same across populations?

A

No - it may vary

70
Q

Can a test have a single level of reliability?

A

No - it is composed of several different kinds - the importance of each type depends on the test

71
Q

What is more important - reliability or validity?

A

Both important, but usually preferable to choose a test of slightly lesser reliability if it can be demonstrated that the test is associated with a meaningfully higher level of validity

72
Q

What does high internal consistency indicate?

A

That the test is measuring a single construct

73
Q

What kind of reliability is considered essential?

A

High test-retest reliability is considered essential unless the test is measuring state variables that are expected to fluctuate

74
Q

How do you interpret a reliability coefficient?

A

A reliability coefficient can be interpreted directly in terms of the percentage of score variance attributed to different scores

75
Q

How do you estimate true score variance?

A

By knowing all the sources of variance (test-retest, alternate form, inter-rater) then you can estimate true score variance

76
Q

What are the 5 categories of reliability coefficient magnitudes?

A
  1. Very high (.90+)
  2. High (.80-.89)
  3. Adequate (.70-.79)
  4. Marginal (.60-.69)
  5. Low (
77
Q

What is a low magnitude reliability coefficient?

A
78
Q

What is a marginal reliability coefficient?

A

.60-.69

79
Q

What is an adequate reliability coefficient?

A

.70-.79

80
Q

What is a high reliability coefficient?

A

.80-.89

81
Q

What is a very high reliability coefficient?

A

.90+

82
Q

What is the important limitation of reliability coefficients?

A

They do not provide complete information on the reproducibility of individual test scores

83
Q

What is a true score?

A

The score an examinee would obtain on a measure in the absence of any measurement error - these are never known, but rather estimated

Conceptually defined as the mean score an examinee would obtain across an infinite number of randomly parallel forms of a test

84
Q

Obtained scores

A

The actual score yielded by the test

Sum of true scores and error

85
Q

Estimated true scores

A

The sum of the mean score of the group and the deviation of the person’s score from the normative mean weighted by test reliability

86
Q

As test reliability approaches unity (r=1.0) estimated true scores approach X

A

Obtained scores

87
Q

As test reliability is close to 0, estimated true scores approach X

A

the mean test scores

88
Q

In the SEM formula what is the kind of reliability it is looking for?

A

reliability coefficient of the test (usually internal reliability)

89
Q

What is validity?

A

the degree to which a test actually measures what it is intended to measure

90
Q

What are the three main types of validity?

A
  1. Content validity
  2. Criterion validity
  3. Construct validity
91
Q

What are two sub-types of content validity?

A
  1. Divergent

2. Convergent

92
Q

What are two sub-types of criterion validity?

A
  1. Concurrent

2. Predictive

93
Q

How do you evaluate construct validity?

A

Correlation with other tests, factor analysis, internal consistency, convergent and discriminant validation, structural equation modelling

94
Q

What is test sensitivity?

A

The proportion of COI+ examinees who are correctly identified as such by a test

(high sensitivity tests yields high levels of correct positives)

95
Q

What is test specificity?

A

The proportion of COI- examinees who are correctly identified as such by a test

(high specificity test yields high levels of correct rejections)

96
Q

What is positive predictive power?

A

The probability that someone with a positive test result has the COI

97
Q

The likelihood that a profile of test scores will exceed criteria for abnormality increases as:

A
  1. The number of tests in a battery increases
  2. The z score cutoff used to classify a test score as abnormal decreases
  3. The number of abnormal test scores required to reach criteria decreases

Psyc 820 - MCQs (16 decks)

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