Soc 497 - Research Methods » Spring 2019 » Chapter 7
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Question #1
A careful, systematic definition of a construct that is explicitly written down.
A.
Discrete Variables
B.
Operational Definition
C.
Conceptual Definition
D.
Conceptualization
Question #2
The process of moving from a construct's conceptual definition to specific activities or measures that allow a researcher to observe it empirically.
A.
Operationalization
B.
Conceptual Definition
C.
Conceptualization
D.
Stability Reliability
Question #3
The definition of a variable in terms of the specific operations or actions a researcher carries out to measure it.
A.
Face Validity
B.
Discrete Variables
C.
Conceptual Definition
D.
Operational Definition
Question #4
Measurement of reliability across time; a measure that yields consistent results at different points assuming what is being measured does not change
A.
Conceptual Definition
B.
Equivalence Reliability
C.
Representative Reliability
D.
Stability Reliability
Question #5
A measure that yields consistent results for various groups or subpopulations.
A.
Stability Reliability
B.
Face Validity
C.
Representative Reliability
D.
Equivalence Reliability
Question #6
A measure that yields consistent results using different specific indicators, assuming that all measure the same thing.
A.
Equivalence Reliability
B.
Stability Reliability
C.
Content Validity
D.
Representative Reliability
Question #7
All these are measures to improve reliability EXCEPT one
A.
Use multiple indicators of a variable
B.
Use pilot studies and replication
C.
Clearly conceptualize all constructs.
D.
conduct extensive research on the topic
E.
Increase the level of measurement
Question #8
A type of measurement validity in which an indicator makes sense as a measure of a construct when judged by others in the scientific community.
A.
Criterion Validity
B.
Content Validity
C.
Face Validity
D.
Convergent Validity
Question #9
A type of measurement validity that requires that a measure represent all aspects of the conceptual definition of a construct.
A.
Face Validity
B.
Content Validity
C.
Criterion Validity
D.
Convergent Validity
Question #10
uses some standard or criteria to indicate a construct accurately
A.
Construct Validity
B.
Criterion Validity
C.
Discriminant Validity
D.
Predictive Validity
Question #11
When an indicator predicts future events that are logically related to the construct.
A.
Face Validity
B.
Predictive Validity
C.
Construct Validity
D.
Criterion Validity
Question #12
an indicator must be associated with a preexisting indicator that is already judged to be valid.
A.
Concurrent Validity
B.
Content Validity
C.
Discriminant Validity
D.
Discriminant Validity
Question #13
A type of measurement validity that relies on some independent, outside verification.
A.
Discriminant Validity
B.
Predictive Validity
C.
Construct Validity
D.
Construct Validity
Question #14
It means that multiple indicators in the same construct will act alike or operate in similar ways.
A.
Convergent Validity
B.
Face Validity
C.
Discriminant Validity
D.
Construct Validity
Question #15
A type of measurement validity for Multiple indicators based on the idea that indicators of different
A.
Discriminant Validity
B.
Construct Validity
C.
Discriminant Validity
D.
Construct Validity
Question #16
Variables that are measured on a continuum and have a large number of values/attributes.
A.
Exhaustive attributes
B.
Likert Scales
C.
Content Validity
D.
Continuous Variables
Question #17
Variables that have a relatively fixed, and limited set of values/attributes.
A.
Mutually Exclusive Attributes
B.
Discrete Variables
C.
Construct Validity
Question #18
A system for organizing information in the measurement of variables
A.
Content Validity
B.
Content Validity
C.
Mutually Exclusive Attributes
D.
Levels of Measurement
Question #19
The lowest, least precise level of measurement for which there is a difference in type only among the categories/attributes of a variable.
A.
Ordinal Level
B.
Continuous Variables
C.
Nominal Level
D.
Criterion Validity
Question #20
A level of measurement that identifies a difference among categories/attributes of a variable and allows the categories to be rank ordered.
A.
Ordinal Level
B.
Mutually Exclusive Attributes
C.
Continuous Variables
D.
Interval Level
Question #21
A level of measurement that identifies differences among variable attributes, ranks categories, and Measures distance between categories, but has no true zero
A.
Ratio Level
B.
Nominal Level
C.
Discrete Variables
D.
Interval Level
Question #22
the highest, most precise level of measurement; variable attributes can be rank ordered, the distance between them precisely measured, and there is an absolute zero.
A.
Ratio Level
B.
Discrete Variables
C.
Nominal Level
D.
Ordinal Level
Question #23
It is one of the principles of good measurement in which the variable attributes or categories in a measure are organized so that responses fit into only one category and there is no overlap.
A.
Nominal Level
B.
Interval Level
C.
Mutually Exclusive Attributes
D.
Ordinal Level
Question #24
The principle that attributes or categories in a measure should provide a category for all possible responses.
A.
Ordinal Level
B.
Exhaustive attributes
C.
Nominal Level
D.
Ratio Level
Question #25
A measure in which a researcher wants to capture the intensity, direction, level, or potency of a variable along a continuum.
A.
Mutually Exclusive Attributes
B.
Concurrent Validity
C.
Exhaustive attributes
D.
Scale
Question #26
These scales are widely used in survey research. They were developed in the 1930’s by Rensis Likert to provide an ordinal-level measure of a person’s attitude.
A.
Predictive Validity
B.
Construct Validity
C.
Likert Scales
D.
Exhaustive attributes
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