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Research methods > 1.10 Measurement > Flashcards

1.10 Measurement Flashcards

1
Q 
#Measurement Process.
Specification of observable referents for concepts of interest?
A

Concept/Construct (Conceptual definition) -> Variable (Operational definition)

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2
Q

Conceptual Definitions?

A

Self-esteem: A person’s overall evaluation of his/her own worth, value, or importance.
Social support: Aid, assistance, or support that is offered in a social relationship and intended to be helpful.

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3
Q

Operational Definitions?

A

-Procedures for assigning cases to values/categories of variables.
-Specifies the activities needed to measure the variable.
+How the data will be obtained
+What questions will be asked or observation will be made
+What the response categories are
+Any other instructions needed

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4
Q

Approaches to Operationalizing Measured Variables?

A
  • Self-reports
  • Observations
  • Archival records
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5
Q

Composite Measures?

A

Measures that combine several indicators into a single index or scale.
Example: Rosenberg Self-Esteem Scale

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6
Q

Self-Esteem?

A
  • Conceptual definition: A person’s overall evaluation of his/her own worth, value, or importance.
  • Operational definition: Respondent’s self-report of self-esteem based on the Rosenberg Self-Esteem Scale (1965)
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7
Q 
#Variables/
Level of Measurement?
A
  • Nominal
  • Ordinal
  • Interval
  • Ratio
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8
Q

Nominal?ex

A
  • Values included 2 or more non-overlapping and exhaustive categories that have no mathematical relation to each other.
  • Ex: gender; race/ethnicity; college major
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9
Q

Ordinal?ex

A
  • Values indicate a rank ordering of the categories.

- Ex: social class (low, middle, high); Self-rated health status (very good, good, bad, very bad)

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10
Q

Interval?ex

A
  • Values indicate categories that are ordered and separated by equal intervals, but there is no true zero.
  • Ex: temperature (Fahrenheit); IQ
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11
Q

Ratio?ex

A
  • Same properties as interval and there is an absolute (non-arbitrary) zero. All mathematical operations are possible.
  • Ex: number years schooling; income (dollars)
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12
Q

Measurement Error?

A

Observed Value= True Value + Error

Observed Value= True Value + Systematic Error+ Random Error

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13
Q

Kind of Measurement Error?

A
  • Systematic error

- Random error

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14
Q

Systematic error?ex

A
  • Due to recurring, systematic factors.
  • Error tends to lean in one direction.
  • Causes systematic distortion (bias) in measurement
  • Example: social desirability bias is the tendency of respondents to answer questions in a manner that will be viewed favorably by others. It can take the form of over-reporting good behavior or under-reporting bad behavior.
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15
Q

Random error?ex

A
  • Due to chance factors
  • Unrelated to true differences in the concept being measured.
  • Error goes in all directions.
  • Presence, direction, and extent are unpredictable
  • Example: ambiguous items, fatigue
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16
Q

Judging the Adequacy/Goodness of Measurement?ex

A

-Reliability
Does the operational definition measure something with consistency and stability?
Is X always X?
-Validity
Does the operational definition measure what it is supposed to measure?
Is X really X?

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17
Q

Effect of Random and Systematic Error on Reliability and Validity?

A
  • Random error affects the reliability of measures as well as the validity because unreliable measures are not valid.
  • Systematic error affects the validity of measures, but not the reliability.
18
Q

Linkage between Reliability and Validity?

A
  • A measure can be reliable and valid.
  • A measure can be reliable but not valid.
  • A measure cannot be unreliable and valid.
  • Reliability is a necessary but not sufficient criterion for validity.
19
Q

Reliability Assessment?

A

-Stability: Test-retest reliability
-Equivalence (for multi-item scale measures)
Split-half reliability
Internal consistency reliability
-Equivalence (for multiple raters/coders/observers): Intercoder reliability

20
Q

Reliability Assessment?

What is assessed
How is it assessed
Example

A
  • Test-Retest Reliability
  • Split-Half Reliability
  • Internal Consistency Reliability
  • Intercoder Reliability
21
Q

Test-Retest Reliability? assess?ex

A
  • Stability: Does a measure provide the same scores when administered on 2 separate occasions to the same group of respondents?
  • Compute correlation coefficient for 2 sets of scores
  • Administered a questionnaire measuring parenting style to a group of parents, then re-administer one month later. Compute correlation coefficient.
22
Q

Split-Half Reliability?assess?ex

A
  • Equivalence: Do 2 halves of a multi-item scale provide similar scores?
  • Compute correlation coefficient for 2 halves of scores (subsets randomly selected)
  • Administer a 30-item scale measuring parenting style, randomly divide into 2 15-item scales, then compute the correlation between the scales.
23
Q

Internal Consistency Reliability?assess?ex

A
  • Equivalence: To what extent are the items in a multi-item scale homogeneous? (i.e., measuring the same concept)?
  • Compute coefficient alpha (e.g., Cronbach’s alpha)
  • Administer a multi-item scale measuring parenting style and compute Cronbach’s alpha.
24
Q

Intercoder Reliability?assess?ex

A
  • Equivalence: To what extent do 2 coders provide the same scores when using the same instrument or measure?
  • Compute percentage agreement between each pair of observers. (or Kappa coefficients)
  • Have social workers observe and code the same parent-child interaction and compare their agreement in coding the interaction.
25
Q

Cronbach’s alpha?

A

Cronbach’s alpha can be written as a function of the number of test items and the average inter-correlation among the items.

26
Q

Cronbach’s alpha formula?

A
  • K is the number of items. r-bar is the average inter-item correlation.
  • If you increase the number of items, you increase Cronbach’s alpha.
  • As the average inter-item correlation increases, Cronbach’s alpha increases as well
  • Cronbach’s alpha reflect the consistent responses of different items
27
Q

Improving Reliability?

A

-Make sure the measure is clearly understood
+Preliminary interviews
+Pretesting
+Focus groups
-Check that the instructions to respondents/interviewers are clear.
-In multi-item scales, assess and remove items that do not hang together with other items.
-Add more items to a multi-item scale.

28
Q

Validity Assessment?

A

-Face Validity
Judgment that a measure appears to measure what it is intended to measure.
-Content Validity
Judgment that a measure’s items cover the universe of things that represent that content.
-Criterion Validity
Concerned with the ability of an index measure to predict a criterion measure.
-Construct Validity
Concerned with the theoretical relationships between a measure and other measures.

29
Q

Content Validity Concept: Parenting Style

A

Should include all of the following dimensions:

  • Warmth
  • Involvement
  • Discipline
  • Expectations
  • Monitoring
30
Q

Criterion Validity?

A
  • One may wish to devise measures that will identify children with learning disabilities, determine a person’s ability to fly an airplane or drive a car
  • The trait or behavior is called a criterion, and validation is a matter of how well scores on the measure correlate with the criterion of interest
31
Q 
#Criterion Validity?
 Measure ->Criterion
A

-SAT test -> College performance
-Driving practices test-> # Tickets received over 5 years
Musical ability-> Foreign language aptitude

32
Q

Criterion Validity? characteristics

A
  • Practical use

- Problems exist

33
Q

Criterion Validity? explain

A

-Practical use: Whether the measure can predict the criterion, not in what the measure means or why it is related to the criterion
-So…..if accuracy in gun shooting correlated with success in college, then gun shooting would be a valid measure for predicting success in college
-Problems exist.
+What standards do you choose the criterion?
+What if no reasonable criterion exists?
+What if the criterion exists but practical problems prevent using it?

34
Q

Construct Validity?

A
  • Interested in the meaning of the concepts being measured
  • Any concept is implied by its theoretical relations to other concepts
  • The validation process begins by examining the theory underlying the concept being measured
35
Q

Construct Validity? 4

A
  1. Correlations with related variables
  2. Convergent validity
  3. Discriminant validity
  4. Known-groups validity
36
Q

Construct Validity

Example: Aggression

A
  • The concept of aggression generally implies destructive or punitive behavior directed toward other persons or objects
  • The self-reported measure of aggression includes 6 items on a 5-point scale ranging from strongly disagree (0) to strongly agree (4). The total score ranges from 0 to 24, with higher values indicating greater aggression. Sample items are:
    (a) Whoever insults me or my family is asking for a fight.
    (b) I can think of no good reason for ever hitting anyone
37
Q

1.Correlations with related variables?

A

The variable should correlate (+/-) with other theoretically related variables. Aggression?
Social competence:-.78
Peer rejection:.69
Association with deviant peers:.72

38
Q

2.Convergent Validity

A

The variable should be correlated with other measures of the same construct measured in different ways. Aggression?
Teacher reports:.80
Parent reports:.75
Observation measure of dyads engaged in task: .78

39
Q

3.Discriminant Validity?

A

The variable should have low or moderate correlations with variables from which it should theoretically differ. Aggression?
Assertiveness:.50
Anxiety:.40
Other examples:Likeness vs. Love

40
Q

4. Known-Groups Validity?

A

Responses to the variable should differ as expected when tested on 2 groups that should differ in their responses based on what is known about them. Aggression (Mean)*?
Juvenile offenders:22
Students assigned to detention:18
Students in regular classroom: 9
*Range =0-24, higher scores mean more aggressive behavior

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