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Content Analysis: Measurement and Validity Kimberly A. Neuendorf, Ph.D. Cleveland State University Fall 2011.

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Presentation on theme: "Content Analysis: Measurement and Validity Kimberly A. Neuendorf, Ph.D. Cleveland State University Fall 2011."— Presentation transcript:

1 Content Analysis: Measurement and Validity Kimberly A. Neuendorf, Ph.D. Cleveland State University Fall 2011

2 Measurement  “Assignment of numerals to objects or events according to rules” (Stevens, 1951)

3 Operationalization (Measurement)  Categories that are exhaustive and mutually exclusive  High and appropriate level of measurement Ratio Interval Ordinal Nominal

4 Evaluating Measures: Comparing Reliability, Accuracy (lack of Bias), and Precision  Targets…also see p. 114 of book.  See also: Carmines, E. G., & Zeller, R. A. (1979). Reliability and validity assessment. Newbury Park, CA: Sage Publications.

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6 High Reliability High Accuracy High Precision

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8 High Reliability Low Accuracy High Precision

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10 Low Reliability Moderate Accuracy High Precision

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12 Reliability? High Accuracy Low Precision

13 Validity  Internal Validity Conceptual definition =matches= Operationalization The standard of having a “good” measure—”Are we hitting the target we want?”  External Validity Generalizability  Sample  Ecological validity  Replicability

14 Validity  “Face” Validity  Criterion Validity Relate to established standard or behavior  Concurrent  Predictive e.g., Oliver & Kalyanaraman (2002) study of sexual and violent content in trailers and films... Criterion is the MPAA rating

15 Validity  Content Validity Construct = ???

16 Validity  Content Validity

17 Validity  Content Validity

18 Validity  Content Validity High internal consistency reliability...

19 Validity  Construct Validity Related to other measures (constructs) in ways consistent with theory  Convergent—relationships as expected  Discriminant—lack of relationships, as expected

20 Construct Validity  Smith volume (1992) on “thematic content analysis”—psychographic applications—has examples Trust-mistrust coding system for TAT stories construct validated against:  Other thematic coding systems (e.g., Affiliation; Intimacy)  Demographics (e.g., Mothers’ feeding habits during infancy (more or less principled), moderated by gender & age)  Self-reported behaviors (e.g., Reported positive relationships with others; Divorce, family fights in last year; Drug use)  Personality measures (e.g., Impulsivity; Locus of Control)

21 Validity Assessment & CATA  Short et al. (2010) provides a model for validity and CATA, using tests of a new dictionary for “entrepreneurial orientation” Content Validity  Deductive  Inductive External Validity Reliability Dimensionality (a type of Construct Validity--Discriminant) Predictive Validity (seems to really be Construct Validity— Convergent???)

22 Validity Assessment & CATA  A Slight Adaptation of Short et al. (2010), converging with Carmines and Zeller (1979): Face Validity Content Validity  Deductive  Inductive External Validity Construct Validity--Dimensionality (Discriminant Validity) Construct Validity--Predictive (Convergent Validity) Criterion Validity (Concurrent or Predictive) [Reliability—separate, but without it, validity is also compromised]

23 Apply to the iCarly Case? (Disrespectful Behaviors)  A Slight Adaptation of Short et al. (2010), converging with Carmines and Zeller (1979): Face Validity Content Validity  Deductive  Inductive External Validity Construct Validity--Dimensionality (Discriminant Validity) Construct Validity--Predictive (Convergent Validity) Criterion Validity (Concurrent or Predictive) [Reliability—separate, but without it, validity is also compromised]

24  pause


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