Tal_Or: Data set testing causal direction in presumed media influence

Description

Nurit Tal-Or, Jonanathan Cohen, Yariv Tasfati, and Albert Gunther (2010) examined the presumed effect of media on other people and change in attitudes. This data set is from Study 2, and examined the effect of presumed influence of the media upon subsequent actions. It is used as an example of mediation by Hayes (2013) and for the mediate function.

Usage

data("Tal.Or")

Arguments

Format

A data frame with 123 observations on the following 6 variables.

cond: Experimental Condition: 0 low media importance, 1 high media importance
pmi: Presumed media influence (based upon the mean of two items
import: Importance of the issue
reaction: Subjects rated agreement about possible reactions to the story (mean of 4 items).
gender: 1 = male, 2 = female
age: a numeric vector

Details

Tal-Or et al. (2010) examined the presumed effect of the media in two experimental studies. These data are from study 2. `... perceptions regarding the influence of a news story about an expected shortage in sugar were manipulated indirectly, by manipulating the perceived exposure to the news story, and behavioral intentions resulting from the story were consequently measured." (p 801).

References

Nurit Tal-Or, Jonathan Cohen, Yariv Tsfati and Albert C. Gunther (2010), Testing Causal Direction in the Influence of Presumed Media Influence, Communication Research, 37, 801-824.

Hayes, Andrew F. (2013) Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. Guilford Press.

Examples

Run this code

data(Tal.Or)
mediate(reaction ~ cond + (pmi), data =Tal.Or,n.iter=50)

Run the code above in your browser using DataLab