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This guide outlines the essential decisions researchers must make during operationalization, emphasizing the complexity of measurement processes. It discusses the dimensions and sub-dimensions of concepts, variations within these dimensions, and various levels of measurement including nominal, ordinal, interval, and ratio. The iterative nature of operationalization is highlighted, along with implications for research clarity and hypothesis alignment. Practical tips for question construction and leveraging existing measures are also provided to enhance reliability and validity.
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Choices During Operationalization • Researchers make a number of key decisions when deciding how to measure a concept • Dimensions and sub-dimensions • Range of variation within dimensions • Categories to represent range • Levels of measurement • Nominal, ordinal, interval, ratio
Operationalization: A deliberative process • Not a simple, linear process • Complicated and fraught with trade-offs • Iterative process with cycles of consideration • Debate over proper measurement is key
Dimensions of the Concept • Creating operational measures forces realization about lack of conceptual clarity • List of possible dimensions may be long • Need to decide which ones are most relevant • Ask which ones are central to the inquiry • Reflect on research hypotheses or theories
Range of Variation • Sense of the upper and lower limits • How much are you willing to combine different people into the same category? • Extremely high and Extremely low may be collapsed • Eg. Income, age, height, etc. • Opposition and support for attitudes • Agreement and disagreement
Variation Between Extremes • Degree of precision • How detailed you need to be in measurement • Eg. Age breaks or Exact age? • Related to purpose of study • Eg. Political Party ID: • Dichotomy: Democrat or Republican • Continuum: 7-point scale w/ “independent-leaner”
Levels of Measurement • Nominal Measures • Ordinal Measures • Interval Measures • Ratio Measures
Nominal Measures • Names for characteristics • Do not Exist along an Explicit continuum • Exhaustive • Mutually Exclusive • Eg. Religious Affiliation • Eg. Place of Birth
Ordinal Measures • Can be logically rank-ordered • Represent relatively more of less of variable • No consistent distance between points of measurement • Not just different from one another • More of less of some attribute • Eg. “Not very important,” “fairly important,” “very important” “Extremely important”
Interval Measures • Consistent distance separating attribute • We can say how much more of an attribute • Logical distance between attributes can be Expressed in meaningful standard intervals • Eg. Temperature • 90 degrees vs. 80 degrees = 10 degree difference • 50 degrees vs. 40 degrees = 10 degree difference • Zero-point is arbitrary
Ratio Measures • In addition to all the properties of nominal, ordinal, and interval measures, ratio measures have a true zero point • Eg. Length of time • Eg. Number of times • Eg. Number of affiliations • Can actually state ratio of one to another • X has twice as many affiliations as Y
What’s that scale? • Style of music in a music video • Number of violent acts in a music video • Whether a music video has violence or not? • High, Medium or Low violence in a music video • Hair color • Number of hairs on your head • Sat scores • Social Security Number
What’s that scale? • A baseball player's batting average • A baseball player's field position • A baseball player's position in the batting order • A baseball player's uniform number • College football rankings • IQ
Types of questions • Multiple choice questions • Agree/disagree questions • Likert questions • Frequency scales • Semantic differential scales • Forced-choice statement pairs • Thermometer feeling scales • Nominal checklists • Ordinal categories • Rank-order questions • Filter questions • Open-ended
Tips on Question Construction • 1. Make questions clear using simple language • 2. Keep questions concise • 3. Provide instructions for answering questions • Don’t assume respondent knows question style • 4. Keep research purpose in mind • Make sure items can answer research question • 5. Don’t ask double-barreled questions • E.g., “How well do you think the current Presidential Administration is handling foreign policy and the war on terrorism?”
More Tips • 6. Avoid leading questions • E.g., “Like most Americans, do you read a newspaper every day?” • 7. Avoid negative questions • E.g., “The U.S. should not invade Iraq” Agree or disagree? • 8. Do not ask questions that require complicated mental calculus • E.g., “In the past 30 days, how many hours have you spent watching television with your family?” • 9. Keep ordering of questions in mind
Using Pre-Existing Measures • It is okay to borrow measures • Cite source of questions to give credit • Benefits of using Existing measures: • Saves work • Pre-tested for reliability/validity • Research becomes cumulative
Pretesting • Clarity in question wording • Are categories: • Exhaustive? • Mutually Exclusive? • Realistic time estimate • Preliminary empirical analysis
