Chapter 10: Measurement Flashcards
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| Types of Data</p>
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| Nominal, Ordinal, Interval, Ratio</p>
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| Reliability</p>
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A measurement scale that provides consistent results over time and if free from random error</p>
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| Three Ways to Assess Reliability</p>
<p style="text-align: center;"> 1. Test-Retest</p> <p style="text-align: center;"> 2. Equivalent Form Reliability</p> <p style="text-align: center;"> 3. Internal Consistency Reliability</p>
Measurement
The process of assigning numbers or labels to obects, persons, states, or events in accordance with specific rules for representing quantities or qualities of attributes.
Rule
A guide that tels the researcher what to do
Concept
An abstract idea generalized from particular facts
Constructs
specific types of concepts that exist at higher levels of abstraction. Examples: Customer satisfaction, brand loyalty, media skepticism, high involvement, etc.
Constitutive Definition
Dictionary definition and its relationship to other constructs
Media skepticism
The degree to which individuals are skeptical toward the reality presented in the mass media.
The Measurement Process
- Identify the concept of interest
- Develop a construct
- a constitutive definition
- operational definition
- measurement scales
- evaluate the reliability and the validity of the scales
- utilize the scales
- Research Findings
Operational Definition
Defines which observable characteristics will be measured and the process for assigning a value to the concept.
Measurement Scale
A set of symbols or numbers such that numbers can be assigned by a rule to the individuals (or their behaviors or attitudes) to whom the scale is applied.
Nominal Scales
Uses numerals with out numeric meaning to identify objects, individuals, events or groups.
Characteristics of Nominal Data
Determination of equality/inequality. Frequency counts, percentages/modes. Divides data into categories.
Ordinal Scales
In addition to identification, the numerals provide information about the relative amount of some characteristic posed by an event, object, etc.
Characteristics of Ordinal Data
Median, mean and variance metrics. Ranking.
Interval Scales
Possesses all the properties of nominal and ordinal scales plus the intervals between consecutie points are equal.
Characteristics of Interval Data
BasiDetermination of equality of intervals, added dimension that the intervals between the data points on scale are equal. Prefer measure of complex concepts/constructs. Uses mean/variance. Ex: Thermometer, Pant size/
Ratio Scale
Incorporates all the properties of nominal, ordinal, and interval scales plus it includes an absolute zero point.
Characteristics of Ratio Data
Determination of equality of ratios, Used when precision instruments are available, All mathematical calculations are used, examples include age, weight, height, population, income, etc…
M = A+E
Measurement = Accuracy + Errors (Random or systematic)
Test-Retest Reliability
Obtained by repeating the measurement using the same instrument under as nearly the same conditions as possible.
Problems with Test-Retest
- Difficult to locate and gain cooperation from respondents for a second testing
- First measurement may alter the second response
- Environmental or personal factors may change
Equivalent Form Reliability
Avoids the test-retest by creating equivalent forms of measurement instrument. Determined by measuring the correlation of the scores on the two instruments.
Problems with Equivalent Form Reliability
- Very difficult to create two totally equivalent forms
- If equivalence can be achieved it may not be worth the cost
Internal Consistency Reliability
Assesses the ability to produce the similar results using different samples to measure a phenomenon.
Equivalence
How much error may be introduced by using different sample of items to measure a phenomenon.
Split-Half Technique
Method of assessing the reliability of as scale by dividing the total set of measurement items in half and correlating the results.
Validity
Degree to which what the researcher was trying to measure was actually measured.
Face Validity
Degree to which a measurement seems to measure what it is supposed to measure.
Content Validity
Representativeness, or sampling adequacy, of the content of the measurement instrument.
Criterion-Related Validity
Degree to which a measurement instrument can predict a variable that is designated a criterion.
Predictive Validity
Degree to which a future level of criterion variable can be forecast by a current measurement scale.
Concurrent Validity
Degree to which another variable, measured at the same point in time is as the variable of interest, can be predicted by the measurement instrument.
Construct Validity
Degree to which a measurement instrument represents and logically connects, via the underlying theory, the observed phenomenon to the construct.
Convergent Validity
Degree of correlation among different measurement instruments that purport to measure the same construct.
Discriminant Validity
Measure of the lack of association among constructs that are supposed to be different.
