MEASUREMENT

Research Methods

University of Massachusetts at Boston

©2011 William Holmes 1

WHAT IS MEASUREMENT?

• Connecting variables with empirical data

• Assessment of presence of characteristic (classification)

• Assessment of how much of a characteristic is present (amount)

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BASIS OF MEASUREMENT

• Definition of variables

• Clarity of definitions

• Examples of variables

• Procedures for classification or assessing amount of a characteristic

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WAYS OF DEFINING VARIABLES

• Written definitions (Nominal)

• Examples (Epistemic)

• Theoretical (Nomothetic)

• Procedural (Operational)

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HOW TO CLARIFY DEFINITIONS

• Focus your definition.

• Have it refer to only one thing.

• Identify what it is not.

• Give examples

• Provide some framework for variable

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PROCEDURES FOR MEASUREMENT

• Decide whether you want to measure the presence of something, different types of something, or amounts of something

• Decide on the Level of Measurement

• Be sure categories are exhaustive, exclusive, and unidimensional

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MEASURE PRESENCE WHEN

• The variable only refers to presence or absence of a single characteristic, or

• The variable refers to a dichotomy of characteristics, or

• The variable provides categories

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MEASURE TYPES WHEN

• The variable refers to a classification, or

• The variable refers to a discrete list, or

• The variable refers to categories of something, or

• The variable is a typology8

MEASURE AMOUNT WHEN

• The variable counts something, or

• The variable refers to a length of time, or

• The variable refers to the amount of something, or

• The variable refers to the degree of something

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LEVELS OF MEASUREMENT

• Nominal/Categorical—presence of characteristics

• Ordinal—ranks of characteristics

• Interval—equal distance between ranks

• Ratio—equal distance and meaningful zero point

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ASSESING RELIABILITY

• Test-Retest Procedure

• Split Halves Procedure

• Inter-Item Correlation Procedure

• Inter-Rater Procedure

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ASSESSING VALIDITY

• Face Validity Method

• Construct Method

• Criterion Method

• Predictive Method

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RECOGNIZING GOOD MEASURES: 1

• Categories are exclusive, don’t overlap

• Categories are exhaustive, cover all possibilities

• Categories are unidimensional, refer to only one thing

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RECOGNIZING GOOD MEASURES: 2

• Categories are clear, easy to understand

• Evidence of reliability is offered

• Evidence of validity is offered

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