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COM 633: Content Analysis Sampling and Units

COM 633: Content Analysis Sampling and Units. Kimberly A. Neuendorf, Ph.D. Cleveland State University Fall 2010. Defining the Population. Researcher fiat!? Let’s discuss. “The set of units to which the researcher wishes to generalize.”

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COM 633: Content Analysis Sampling and Units

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  1. COM 633: Content AnalysisSampling and Units Kimberly A. Neuendorf, Ph.D. Cleveland State University Fall 2010

  2. Defining the Population • Researcher fiat!? Let’s discuss. • “The set of units to which the researcher wishes to generalize.” • Is a full sampling frame available? (e.g., population may be defined by a NEXIS search)

  3. Population & Sample

  4. Units

  5. Units

  6. Units

  7. Units

  8. Units

  9. Units

  10. Unitizing • Unit—one decision rule might be to select the “smallest identifiable unit for which one can reliably code for the desired variables, thus providing maximal variance for these measures across the entire unit of sampling” (p. 72) • Coder unitizing vs. a priori unitizing • Unitizing reliability is necessary when coders unitize

  11. Archives • Unprecedented access to “archives” online! • Comprehensive vs. Selective • Electronic/online vs. non • Free vs. costly

  12. Medium Management • Archiving messages • Searching for messages • Preparation of messages for coding/handling during coding • Automated content analysis

  13. Medium Management • A changing area. . . More later in the term

  14. Sampling • Random or Probability Sampling • Simple random sampling (SRS) • Systematic sampling • --------------------------------- • Cluster sampling • Stratified sampling • Multistage sampling

  15. Sampling • Non-probability (nonrandom) Sampling • Convenience sampling • Purposive or judgment sampling • Quota sampling

  16. Sample Size • Rules of thumb • At least 100 • A “rich range” on the variables of interest • Can use desired confidence interval to set sample size (but many formulae—Riffe, Lacy and colleagues have provided some examples)

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