Categorical Statistics for Communication Research by Bryan E. Denham

By Bryan E. Denham

Categorical information for CommunicationResearch offers students with a discipline-specific consultant to express information research. The textual content blends precious historical past details and formulation for statistical strategies with information analyses illustrating ideas resembling log- linear modeling and logistic regression analysis.

  • Provides strategies for interpreting specific information from a conversation stories perspective
  • Provides an available presentation of concepts for examining specific facts for verbal exchange students and different social scientists operating on the complex undergraduate and graduate educating levels
  • Illustrated with examples from varieties of communique learn equivalent to well-being, political and activities conversation and entertainment
  • Includes routines on the finish of every bankruptcy and a better half web site containing workout solutions and chapter-by-chapter PowerPoint slides

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841, indicating a significant relationship between time frame and mentions of drug use in newspaper reports. Again, the researcher would want to double‐ check the direction of variable relationships. Cramér’s V In 1946 Harald Cramér extended phi to larger contingency tables. His statistic, Cramér’s V, is perhaps the most popular measure of association for nominal variables and can be calculated using the following formula, where k can be either a row or column, whichever is smallest: V 2 n k 1 The value of Cramér’s V ranges between 0 and 1, with coefficients closest to 1 indicating comparatively strong relationships.

1, one would observe a conditional association if a significant relationship emerged between mentions of horse injuries/horse deaths and time period in The New York Times or the Los Angeles Times. 0. In a three‐dimensional contingency table, a marginal table contains cross‐ classified data summed across a third measure. 1, the marginal table contains 489 observations, reflecting 320 reports in The New York Times and 169 in the Los Angeles Times. A marginal association occurs when a bivariate relationship emerges in the marginal table.

Gibbons (1993, 73) presented the following formula for Somers’ d, indicating A as the independent variable: dB . 8, Somers’ d would be calculated in the following manner, with n representing the table total and fi representing column totals: dB . 34, indicating a moderate relationship between the two variables. Points of Concern in Bivariate Analyses In a classic article addressing mistakes made by researchers who had used chi‐ square analysis, Lewis and Burke (1949) identified nine sources of error: (1) lack of independence among single events or measures; (2) small theoretical frequencies; (3) neglect of frequencies of non‐occurrence; (4) failure to equalize the sum of the observed frequencies and the sum of the theoretical frequencies; (5) indeterminate theoretical frequencies; (6) incorrect or questionable categorizing; (7) use of non‐frequency data; (8) incorrect determination of the number of degrees of freedom; and (9) incorrect computations.

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