Statistical Methods for Communication Science

By J. Romeu. Technometrics, 2006

392 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/72bee2a80b07a6fc3243b654b1720dcfba925551

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Citations in the corpus

Multiple Oppressions and the Mental Health of Sexual Minority Latina/o Individuals (2015, background): “In each of these three analyses, the four predictors and the three significant interaction effects were included (Hayes, 2005), with simple slopes calculated for the specific interaction effect of focus.”
The Mutual Reinforcement of Media Selectivity and Effects: Testing the Reinforcing Spirals Framework in the Context of Global Warming (2014, neutral): “Although we therefore should be cautious in generalizing the results of our study to the U.S. population, generalizability may be less of a concern given our focus on testing theoretically driven communication processes (see Hayes, 2005).”
Legitimacy through CSR disclosures? The advantage outweighs the disadvantages (2016, background): “In this paper, the text-building lock concept allows us to understand the experiment’s stimulus variable at ordinal level because it scales the “Extent of CSR isclosure” (Hayes, 2005; pp. 20–23).”
Answering the Call for a Standard Reliability Measure for Coding Data (2007, background): “Hayes, 2005), reproducible, and trustworthy. Choosing an index of reliability is complicated by the number of indexes that have been proposed. For example, Popping (1988) compared an astounding 43 measures for nominal data, mostly applicable to reliability data generated by only two observers.”
Living in an age of online incivility: examining the conditional indirect effects of online discussion on political flaming (2014, background): “However, because our goal is to test a theoretical communication process model, the generalizability of our sample is of less importance (Hayes, 2005; Mook, 1983).”
Portrayals of Male and Female Scientists in Television Programs Popular Among Middle School-Age Children (2010, background): “Hayes (2005) suggests that levels as low as .”
Understanding Public Hurricane Evacuation Decisions and Responses to Forecast and Warning Messages (2016, background): “8 The effect sizes reported in this article are squared semipartial correlations, which represent the proportion of the total variance in the dependent variable that is uniquely explained by each independent variable, controlling for all other independent variables (Hayes 2005).”
Contemporary approaches to assessing mediation in communication research. (2008, methodology): “There are many measures of unstandardized and standardized effect size that can be employed in various analyses (e.g., R2 or the squared semipartial correlation in regression, and η2 or ω2 in ANOVA; see, e.g., Hayes, 2005).”
Boomerang Effects in Science Communication (2012, methodology): “Interaction terms with political partisanship were created for both message conditions and entered into the model (following the recommendation of Hayes, 2005, the variables are not mean centered), with regression diagnostics indicating multicollinearity within acceptable tolerances (variance…”
Psychological Reactance From Reading Basic Facts on Climate Change: The Role of Prior Views and Political Identification (2018, background): “ested in making process inferences rather than population inferences (Hayes, 2009).”
Partisan Provocation: The Role of Partisan News Use and Emotional Responses in Political Information Sharing in Social Media (2016, methodology): “significance tests are using about 67% of the information of this predictor, which is generally acceptable in behavioral research (Baguley, 2012; Hayes, 2005).”
How to Measure Generalized Trust in News Media? An Adaptation and Test of Scales (2019, methodology): “As indicators for the model fit of the CFA, we follow the recommendation by Hu and Bentler (1999) and report the Tucker-Lewis index (TLI, sometimes called the non-normed fit index, NNFI) and the standardized root mean square residual (SRMR).”
Computational procedures for probing interactions in OLS and logistic regression: SPSS and SAS implementations (2009, background): “…for F is the estimated effect of F when M , and the estimated standard error for this effect will be the same as that produced by Equation 6 (see Aiken & West, 1991, pp. 18–19; Darlington, 1990, pp. 325–326; Hayes, 2005, pp. 457–458; Irwin & McClelland, 2001; Jaccard & Turrisi, 2003, p. 27).”