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.
Conceptualization
D.
Conceptual Definition
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.
Stability Reliability
B.
Operationalization
C.
Conceptual Definition
D.
Conceptualization
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.
Stability Reliability
C.
Representative Reliability
D.
Equivalence Reliability
Question #5
A measure that yields consistent results for various groups or subpopulations.
A.
Representative Reliability
B.
Face Validity
C.
Equivalence Reliability
D.
Stability Reliability
Question #6
A measure that yields consistent results using different specific indicators, assuming that all measure the same thing.
A.
Representative Reliability
B.
Stability Reliability
C.
Content Validity
D.
Equivalence Reliability
Question #7
All these are measures to improve reliability EXCEPT one
A.
Clearly conceptualize all constructs.
B.
conduct extensive research on the topic
C.
Increase the level of measurement
D.
Use pilot studies and replication
E.
Use multiple indicators of a variable
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.
Content Validity
B.
Criterion 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.
Convergent Validity
B.
Face Validity
C.
Criterion Validity
D.
Content Validity
Question #10
uses some standard or criteria to indicate a construct accurately
A.
Criterion Validity
B.
Predictive Validity
C.
Construct Validity
D.
Discriminant Validity
Question #11
When an indicator predicts future events that are logically related to the construct.
A.
Construct Validity
B.
Face Validity
C.
Predictive Validity
D.
Criterion Validity
Question #12
an indicator must be associated with a preexisting indicator that is already judged to be valid.
A.
Discriminant Validity
B.
Content Validity
C.
Concurrent Validity
D.
Discriminant Validity
Question #13
A type of measurement validity that relies on some independent, outside verification.
A.
Construct Validity
B.
Discriminant Validity
C.
Predictive 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.
Construct Validity
C.
Discriminant Validity
D.
Face 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.
Content Validity
B.
Exhaustive attributes
C.
Continuous Variables
D.
Likert Scales
Question #17
Variables that have a relatively fixed, and limited set of values/attributes.
A.
Construct Validity
B.
Mutually Exclusive Attributes
C.
Discrete Variables
Question #18
A system for organizing information in the measurement of variables
A.
Levels of Measurement
B.
Mutually Exclusive Attributes
C.
Content Validity
D.
Content Validity
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.
Criterion Validity
B.
Ordinal Level
C.
Nominal Level
D.
Continuous Variables
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.
Continuous Variables
B.
Interval Level
C.
Ordinal Level
D.
Mutually Exclusive Attributes
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.
Discrete Variables
B.
Nominal Level
C.
Interval Level
D.
Ratio 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.
Discrete Variables
B.
Ratio Level
C.
Ordinal Level
D.
Nominal 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.
Ordinal Level
B.
Nominal Level
C.
Interval Level
D.
Mutually Exclusive Attributes
Question #24
The principle that attributes or categories in a measure should provide a category for all possible responses.
A.
Ratio Level
B.
Ordinal Level
C.
Nominal Level
D.
Exhaustive attributes
Question #25
A measure in which a researcher wants to capture the intensity, direction, level, or potency of a variable along a continuum.
A.
Concurrent Validity
B.
Mutually Exclusive Attributes
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.
Likert Scales
B.
Construct Validity
C.
Predictive Validity
D.
Exhaustive attributes
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