1. Content Analysis: Sampling & Units Kimberly A. Neuendorf, Ph.D. Cleveland State University Fall 2011

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 PopulationSample The study of its unitsCensusSurvey, experiment, or content analysis The number of unitsNn A summary number about a variable and its distribution ParameterStatistic The mean of a variableµM or X-bar The standard deviation of a variable σsd The variance of a variable σ2σ2 sd 2

4. Units Weyls (2001); study of adult entertainment Lombard et al. (1996); study of TV production techniques Unit of sampling Unit of data collection Unit of analysis

5. Units Weyls (2001); study of adult entertainment Lombard et al. (1996); study of TV production techniques Unit of sampling News story Unit of data collection News story Unit of analysisYear

6. Units Weyls (2001); study of adult entertainment Lombard et al. (1996); study of TV production techniques Unit of sampling News storyTime, date, channel Unit of data collection News storyEpisode, time interval, etc. Unit of analysisYearEpisode, time interval, etc.

7. Units National Cancer Institutes (2003); study of news about mammography Janstova (2006); study of films by Jane Campion vs. others Unit of sampling Unit of data collection Unit of analysis

8. Units National Cancer Institutes (2003); study of news about mammography Janstova (2006); study of films by Jane Campion vs. others Unit of sampling News story Unit of data collection Story, attribution Unit of analysis News story

9. Units National Cancer Institutes (2003); study of news about mammography Janstova (2006); study of films by Jane Campion vs. others Unit of sampling News storyFilm Unit of data collection Story, attributionFilm, character, 5-min. interval Unit of analysis News storyFilm, character, 5-min. interval

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 BUT—How to assess unitizing reliability?  Krippendorff (2004) has begun to look at this

11. Sampling  Random or Probability Sampling “Every element in the population has an equal (or known) chance of selection” Basic types:  Simple random sampling (SRS)  Systematic sampling Variations on these types:  Cluster sampling  Stratified sampling  Multistage sampling

12. Sampling  Non-probability (nonrandom) Sampling Convenience sampling Purposive or judgment sampling Quota sampling

13. 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)

14.  pause