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.
Conceptual Definition
C.
Operational 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.
Stability Reliability
B.
Conceptualization
C.
Operationalization
D.
Conceptual Definition
Question #3
The definition of a variable in terms of the specific operations or actions a researcher carries out to measure it.
A.
Discrete Variables
B.
Face Validity
C.
Operational Definition
D.
Conceptual 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.
Stability Reliability
B.
Representative Reliability
C.
Conceptual Definition
D.
Equivalence Reliability
Question #5
A measure that yields consistent results for various groups or subpopulations.
A.
Equivalence Reliability
B.
Representative Reliability
C.
Stability Reliability
D.
Face Validity
Question #6
A measure that yields consistent results using different specific indicators, assuming that all measure the same thing.
A.
Content Validity
B.
Stability Reliability
C.
Equivalence Reliability
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.
conduct extensive research on the topic
D.
Clearly conceptualize all constructs.
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.
Face Validity
C.
Content 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.
Content Validity
B.
Criterion Validity
C.
Convergent Validity
D.
Face Validity
Question #10
uses some standard or criteria to indicate a construct accurately
A.
Predictive Validity
B.
Discriminant Validity
C.
Criterion Validity
D.
Construct Validity
Question #11
When an indicator predicts future events that are logically related to the construct.
A.
Construct Validity
B.
Face Validity
C.
Criterion Validity
D.
Predictive Validity
Question #12
an indicator must be associated with a preexisting indicator that is already judged to be valid.
A.
Discriminant Validity
B.
Concurrent Validity
C.
Discriminant Validity
D.
Content 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.
Discriminant Validity
B.
Face Validity
C.
Convergent 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.
Likert Scales
B.
Continuous Variables
C.
Content Validity
D.
Exhaustive attributes
Question #17
Variables that have a relatively fixed, and limited set of values/attributes.
A.
Discrete Variables
B.
Mutually Exclusive Attributes
C.
Construct Validity
Question #18
A system for organizing information in the measurement of variables
A.
Mutually Exclusive Attributes
B.
Content Validity
C.
Content Validity
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.
Criterion Validity
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.
Ordinal Level
B.
Mutually Exclusive Attributes
C.
Interval Level
D.
Continuous Variables
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.
Interval Level
D.
Discrete Variables
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.
Nominal Level
B.
Ordinal Level
C.
Ratio Level
D.
Discrete Variables
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.
Interval Level
B.
Ordinal Level
C.
Nominal 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.
Nominal Level
C.
Exhaustive attributes
D.
Ordinal 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.
Exhaustive attributes
B.
Mutually Exclusive Attributes
C.
Concurrent Validity
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.
Exhaustive attributes
C.
Construct Validity
D.
Likert Scales
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