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DATA, VARIABLES, AND CONCEPTS

Learn how to define, operationalize concepts, and measure variables in political science research. Explore the stages of measurement and key challenges in translation. Discover the significance of identifying units of analysis and creating operational definitions to ensure validity and reliability in measurements.

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DATA, VARIABLES, AND CONCEPTS

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  1. DATA, VARIABLES, AND CONCEPTS

  2. READINGS • Pollock, Essentials, preface, introduction, and ch. 1 • Course Reader, Selection 1 (Smith, Cycles of Electoral Democracy)

  3. OUTLINE: THE PROCESS OF MEASUREMENT • The Analytical Challenge: Uncovering Relationships between Concepts • Stage I: Defining Concepts • Stage II: Operationalizing Concepts • Stage III: Variables and Levels of Measurement [next time]

  4. PRIMARY GOALS OF POLITICAL SCIENCE: Describing concepts and analyzing relationships between them. (Example: Degrees of democracy in Latin America and levels of economic development.) A KEY CHALLENGE IN POLITICAL SCIENCE: Translating abstract concepts into concrete terms—to express vague ideas in such as way that they can be described and analyzed.

  5. STAGE ONE: DEFINING CONCEPTS • Identifying the concept—i.e., the topic of research (e.g., democracy, justice, competition, religiosity) • (b) Providing a conceptual definition—clearly describing the properties of the concept

  6. DEFINING CONCEPTS • Think of polar opposites • Select most significant attributes • TEMPLATE: • The concept of ______ is defined as the extent to which ________ exhibit the characteristic of __________. • EXAMPLE: • The concept of religiosity is defined as the extent to which individuals exhibit the characteristic of attending religious services.

  7. ON UNITS OF ANALYSIS: Unit of analysis = the entity (person, city, country, bureaucracy, etc.) we want to describe and analyze Individual-level unit of analysis deals with individuals; Aggregate-level unit of analysis deals with collections of individuals Bewarethe ecological fallacy! arising from use of aggregate-level phenomena to make inferences at the individual level. (Example: left-wing votes in upper-class neighborhoods.)

  8. STAGE TWO: OPERATIONAL DEFINITIONS • Creating an operational definition—proposing the • instrument to be used in measuring the conceptual • definition, putting it “into operation” • (b) Producing variables—which record the actual • measurement of the concept.

  9. An operational definition describes how the concept is to be measured empirically. Validity is the degree to which the operational definition measures the characteristic described in the conceptual definition, and only that characteristic. Reliability is the extent to which the operational definition is a consistent measure of the concept—i.e., containing no random error.

  10. COMPONENTS OF MEASUREMENT: Measurement = Intended characteristic + Systematic error + Random Error

  11. ASSESSING VALIDITY • Face validity • Construct validity (does it behave the way it “should”?)

  12. ASSESSING CONCEPT VALIDITY I: Party % Engaging in Identification Campaign Activity Strong Democrat 53 Weak Democrat 34 Independent/Democrat 43 Independent 28 Independent/Republican 47 Weak Republican 43 Strong Republican 57

  13. ASSESSING CONCEPT VALIDITY II: SCIENCE AND BASEBALL • Question: What’s the most accurate measure of effectiveness? • Conventional wisdom: Batting average, Slugging average, Stolen bases • Revised view: • On-base percentage (including walks as well as hits) • OPS: On-base plus slugging • “Runs Created” = (Hits + Walks) x Total Bases/(At Bats + Walks)

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