Brainscape's Knowledge GenomeTM

Browse over 1 million classes created by top students, professors, publishers, and experts.


See full index

Evidence-Based Management > Chapter 12 & 13 - Measurement of Variables > Flashcards

Chapter 12 & 13 - Measurement of Variables Flashcards

1
Q

Four levels of measurement

A

Nominal
Ordinal
Interval
Ratio

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

Categorical levels of measurement

A

Nominal
Ordinal

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

Continuous levels of measurement

A

Interval
Ratio

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

Nominal level of measurement

A

Identification; classification

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

Ordinal level of measurement

A

Ranking of categories, but not equidistant (at equal distances)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

Interval level of measurement

A
  • Equidistant (at equal distances) ranking, but zero point not fixed
  • Likert-type scales: Ordinal or interval?
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

Ratio level of measurement

A

Possesses a unique origin (zero point)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

Rating Scale Formats

A

– Dichotomous/binary scale
– Category scale
– Semantic differential scale
– Numerical scale
– Itemized rating scale
– Likert-type scale
– Fixed or constant sum scale
– Stapel scale
– Consensus scale
– Graphic rating scale
– Paired comparison scale
– Forced choice scale
– Comparative scale

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

Dichotomous/binary scale rating scale example

A

Yes vs. No

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

Category scale rating scale example

A

English; French; Other

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

Semantic differential scale rating scale example

A

Good —– Bad; Emotionally stable —– Neurotic

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

Numerical scale rating scale example

A

Responsive 1 2 3 4 5 6 7 Unresponsive

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

Itemized rating scale rating scale example

A

Can be balanced or unbalanced; forced or unforced

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

Likert-type scale rating scale example

A
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

Fixed or constant sum scale rating scale example

A

distributing 100 points across several items (need to add
up to 100)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

Stapel scale rating scale example

A

-3 -2 -1 Interpersonal skills +1 +2 +3

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
17
Q

Consensus scale rating scale example

A

Developed by consensus by a panel of judges

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
18
Q

Graphic rating scale rating scale example

A
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
19
Q

Paired comparison scale rating scale example

A

Respondents asked to choose between two objects at a time
(among a small number of objects)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
20
Q

Forced choice scale rating scale example

A

Ranking objects among the provided alternatives

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
21
Q

Comparative scale rating scale example

A

Provides a point of reference to assess attitudes toward a
particular object/event/situation

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
22
Q

Response-scale format considerations

A

– Measurement scale (nominal, ordinal, interval, ratio)
– Number of scale points/categories
* Need to be mutually exclusive and collectively exhaustive
– Balanced or unbalanced scales
* Equal # of favourable & unfavourable categories?
– Forced or non-forced choice
* “Neutral” category
* Odd or even number of categories
– Category labels for scales (anchors)
* Verbal; numerical; unlabeled (e.g., graphic)
– Number of items in a scale

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
23
Q

Operationalization of variables

A

Breaking an abstract construct down to its measureable or
tangible components
* Can tap into a construct by looking at the behavioural dimensions, facets, and properties denoted by the construct and translating them into observable/measurable elements

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
24
Q

Delineating the antecedents, consequences, or correlates of the construct is not _______________

A

operationalization

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
25
Q

Steps in the Operationalization of variables

A
  • Clear definition of the construct (and possibly its dimensions)
  • Develop a pool of items (indicators or elements) representing more concrete manifestations or operalizations of the construct
  • Choose a response format (e.g., Likert-type scale)
  • Collect data from a (representative) sample
  • Conduct item analyses and select items for the scale(s)
  • Test the reliability and validity of the scale(s)
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
26
Q

Typical process in Developing Scales

A

– Define the concept to be measured
– Identify components/elements of the concept
– Specify sample of observable, measurable items representing the components/elements of the concept
– Select an appropriate response format to measure the items
– Combine the items into a composite (summated) scale
– Pretest the scale to assess respondent understanding
– Assess scale reliability and validity
– Revise the scale (if needed)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
27
Q

considerations for evaluating existing scales

A

– Title, author(s), publisher (if applicable)
– Language(s); equivalence of translated forms
– Construct(s) (allegedly) measured
– Characteristics of development/normative sample(s)
– Costs/permissions required
– User qualifications
– Format; administration method; scoring; length/time
– Psychometrics: Evidence of reliability, validity, fairness
– Independent reviews or peer-reviewed research

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
28
Q

____________ Consist of a number of closely related
items (questions or statements) whose
responses are combined into a composite
score to measure a construct

A

Multi-Item (Summated) Scales

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
29
Q

Recommendations for Multi-Item (Summated) Scales

A

Items should be closely related, represent only
a single construct, and represent the construct
completely

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
30
Q

Assessing Measurement Scales

A

Reliability
Validity (unitary)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
31
Q

Assessing Measurement Scales - Reliability

A
  • Test-retest reliability
  • Parallel-form reliability
  • Inter-rater reliability
  • Internal consistency reliability
  • Split-half reliability
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
32
Q

Assessing Measurement Scales - Validity (unitary)

A
  • Content validity
  • Construct validity
  • Convergent validity
  • Discriminant validity
  • Criterion-related validity
  • Concurrent validity
  • Predictive validity
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
33
Q

Reliability

A

the stability and consistency of scores generated by a scale

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
34
Q

Stability of scores (derived from scales)

A

– Test-retest reliability (stability over time)
– Parallel-form reliability (stability across forms)
– Administer them to the same subjects
– Inter-rater reliability (stability across raters)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
35
Q

Inter-item (or internal) consistency reliability

A
  • Consistency of answers to all the items in a measure
    – If these items independently measure the same concept,
    they will be highly correlated
  • Coefficient α or Cronbach’s α
    – A different “alpha” than the one associated with Type I error
  • Rule of thumb: Use α >.70 as “acceptable” in our field
36
Q

Split-half reliability

A
  • Correlations between two halves of an instrument
  • Typically not as useful as Cronbach’s α
37
Q

Validity

A

whether an instrument measures what it sets out to measure

38
Q

Construct validity

A

Degree of correspondence between a construct and its
operational definition (measure or manipulation)

39
Q

Forms of evidence in validity

A
  • Content-based (content validity)
  • Convergent and discriminant validity
  • Criterion-related evidence (concurrent and predictive)
40
Q

Content validity

A

Evidence that the content of a test corresponds to
the content of the construct it was designed to
measure
* Usually relies on opinions of subject matter experts

41
Q

Face validity

A

Does the scale appear to measure the
construct?

42
Q

Convergent validity

A

– Identify another scale that measures the same
construct as the one being validated
– Obtain scores on both scales and compute the
correlation between them (should be high)

43
Q

Discriminant validity

A

– Identify a scale that measures a different construct
– Specify how the two scales are expected to differ
– Obtain scores on both scales and compute the correlation between them (should be low)

44
Q

Convergent and discriminant validity

A

Professional credentialing examinations are designed to assess the knowledge required for competent professional practice in a given discipline.

45
Q

Measurement

A

The assignment of numbers or other symbols to characteristics (or attributes) of objects according to a prespecified set of rules.

46
Q

Operationalizing

A

Reduction of abstract concepts to render them measurable in a tangible way.

47
Q

Some considerations for evaluating existing scales

A

– Title, author(s), publisher (if applicable)
– Language(s); equivalence of translated forms
– Construct(s) (allegedly) measured
– Characteristics of development/normative sample(s)
– Costs/permissions required
– User qualifications
– Format; administration method; scoring; length/time
– Psychometrics: Evidence of reliability, validity, fairness
– Independent reviews or peer-reviewed research

48
Q

Multi-Item (Summated) Scales

A

Consist of a number of closely related
items (questions or statements) whose
responses are combined into a composite
score to measure a construct
– Scale / Index / Summated rating scale /
Multi-item scale

49
Q

Scale

A

A tool or mechanism by which individuals, events, or objects are distinguished on the variables of interest in some meaningful way.

50
Q

Likert scale

A

An interval scale that specifically uses the five anchors of
Strongly Disagree, Disagree, Neither Disagree nor Agree, Agree, and Strongly Agree.

51
Q

Nominal scale

A

A scale that categorizes individuals or objects into mutually
exclusive and collectively exhaustive groups, and offers basic,
categorical information on the variable of interest.

52
Q

Ordinal scale

A

A scale that not only categorizes the qualitative differences in the variable of interest, but also allows for the rank‐ordering of these categories in a meaningful way.

53
Q

Interval Scale

A

A multipoint scale that taps the differences, the order, and the
equality of the magnitude of the differences in the responses

54
Q

Ratio scale

A

A scale that has an absolute zero origin, and hence indicates not only the magnitude, but also the proportion, of the differences.

55
Q

Rating scale

A

Scale with several response categories that evaluate an object on a scale.

56
Q

Ranking Scale

A

Scale used to tap preferences between two or among more objects or items

57
Q

Dichotomous scale

A

Scale used to elicit a Yes/No response, or an answer to two
different aspects of a concept.

58
Q

Category scale

A

A scale that uses multiple items to seek a single response.

59
Q

Semantic differential scale

A

Usually a seven‐point scale with bipolar attributes indicated at its extremes.

60
Q

Numerical scale

A

A scale with bipolar attributes with five points or seven points
indicated on the scale.

61
Q

Unbalanced rating scale

A

An even‐numbered scale that has no neutral point.

62
Q

Faces scale

A

A particular representation of the graphic scale, depicting faces with expressions that range from smiling to sad.

63
Q

Consensus scale

A

A scale developed through consensus or the unanimous
agreement of a panel of judges as to the items that measure a concept.

64
Q

Constant sum rating scale

A

A scale where the respondents distribute a fixed number of points across several items.

65
Q

Paired comparisons

A

Respondents choose between two objects at a time, with the
process repeated with a small number of objects.

66
Q

Forced choice

A

Elicits the ranking of objects relative to one another.

67
Q

Comparative scale

A

A scale that provides a benchmark or point of reference to assess attitudes, opinions, and the like.

68
Q

Reliability

A

Attests to the consistency and stability of the measuring
instrument.

69
Q

Validity

A

Evidence that the instrument, technique, or process used to
measure a concept does indeed measure the intended concept.

70
Q

Goodness of measures

A

Attests to the reliability and validity of measures.

71
Q

Content validity

A

Establishes the representative sampling of a whole set of items that measures a concept, and reflects how well the dimensions and elements thereof are delineated.

72
Q

Face validity

A

An aspect of validity examining whether the item on the scale, on the face of it, reads as if it indeed measures what it is supposed to measure.

73
Q

Criterion-related validity

A

That which is established when the measure differentiates
individuals on a criterion that it is expected to predict.

74
Q

Concurrent validity

A

Relates to criterion‐related validity, which is established at the same time the test is administered.

75
Q

Predictive validity

A

The ability of the measure to differentiate among individuals as to a criterion predicted for the future.

76
Q

Construct validity

A

Testifies to how well the results obtained from the use of the
measure fit the theories around which the test was designed.

77
Q

Convergent validity

A

That which is established when the scores obtained by two
different instruments measuring the same concept, or by
measuring the concept by two different methods, are highly
correlated.

78
Q

Discriminant validity

A

That which is established when two variables are theorized to be uncorrelated, and the scores obtained by measuring them are indeed empirically found to be so.

79
Q

Test–retest reliability

A

A way of establishing the stability of the measuring instrument by correlating the scores obtained through its administration to the same set of respondents at two different points in time.

80
Q

Parallel‐form reliability

A

That form of reliability which is established when responses to two comparable sets of measures tapping the same construct are highly correlated.

81
Q

Internal consistency

A

Homogeneity of the items in the measure that tap a construct.

82
Q

Inter item consistency reliability

A

A test of the consistency of responses to all the items in a measure to establish that they hang together as a set.

83
Q

Split‐half reliability

A

The correlation coefficient between one half of the items
measuring a concept and the other half.

84
Q

Reflective scale

A

Each item in a reflective scale is assumed to share a common
basis (the underlying construct of interest).

85
Q

Formative scale

A

Used when a construct is viewed as an explanatory combination of its indicators.

86
Q
A

Evidence-Based Management (20 decks)

Brainscape helps you reach your goals faster, through stronger study habits.
© 2024 Bold Learning Solutions. Terms and Conditions