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Environmental Concern, Patterns of Television Viewing, and Pro-Environmental Behaviors
Unformatted Document Text:  TV-Environment 11 We also included two contextual variables in the exogenous portion of our regression equations, home ownership and population density. Home ownership is a dichotomous measure (Own home coded high). Population density is a seven-item measure constructed from Census data. Several researchers have studied the influence of home ownership on environmental conditions of neighborhoods (e.g., Arblaster & Hawtin, 1993), and there has also been work on the influence of the urban versus rural dichotomy on a range of matters pertaining to the environment (e.g., Jones, Fly, & Cridell, 1999; Van Liere & Dunlap, 1980). Finally, we included a single orientation variable, ideology. This item was measured with a single response to a five-point scale, “Generally speaking, would you consider yourself to be…,” with the scale ranging from (very conservative) to (very liberal). Recent work reinforces the argument that support for environmental policies falls along ideological lines (e.g., Shipan & Lowry, 2001). Analyses Our analyses consist of three components. First, OLS regression path analysis was used to test an identical model for each year, 1999 and 2000. The eight demographic, situational, and orientational variables were entered in a first block, followed by a second block consisting of the single attitudinal measure of environmental concern. The five forms of television use first served as criterion variables. Following this, they were entered simultaneously in a third block, with pro-environmental behaviors as the criterion variable. Second, each form of television use found to be significant predictors of pro-environmental behaviors in the path analyses were entered separately in a block after all other variables in each equation. The incremental R 2 statistic was used to formally test whether the various forms of media use retained a unique relationship with the criterion variable beyond that which had already been established by the other variables in the equation. Third, we used a stringent method for replication assessment outlined by Rosenthal (1991) to formally cross-validate our results across the two data sets. Rosenthal argues against judging the success of a replication in a dichotomous fashion based on the emergence of similar statistical significance levels. Instead, he contends that researchers should make a final judgment concerning a replication’s success along a continuum and via a comparison of the effects sizes. As noted by Jegerski (1991), “the abandonment of the p-value for comparing replications is appropriate and long overdue” (p. 37). Accordingly, the tests for the incremental R 2 ’s served as the assessment tool for the merit of our replication (see Rosenthal [1984] for conversion equations).

Authors: Holbert, R. Lance., Kwak, Nojin. and Shah, Dhavan.
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TV-Environment 11
We also included two contextual variables in the exogenous portion of our regression equations, home
ownership and population density. Home ownership is a dichotomous measure (Own home coded high). Population
density is a seven-item measure constructed from Census data. Several researchers have studied the influence of
home ownership on environmental conditions of neighborhoods (e.g., Arblaster & Hawtin, 1993), and there has also
been work on the influence of the urban versus rural dichotomy on a range of matters pertaining to the environment
(e.g., Jones, Fly, & Cridell, 1999; Van Liere & Dunlap, 1980).
Finally, we included a single orientation variable, ideology. This item was measured with a single response
to a five-point scale, “Generally speaking, would you consider yourself to be…,” with the scale ranging from (very
conservative) to (very liberal). Recent work reinforces the argument that support for environmental policies falls
along ideological lines (e.g., Shipan & Lowry, 2001).
Analyses
Our analyses consist of three components. First, OLS regression path analysis was used to test an identical
model for each year, 1999 and 2000. The eight demographic, situational, and orientational variables were entered
in a first block, followed by a second block consisting of the single attitudinal measure of environmental concern.
The five forms of television use first served as criterion variables. Following this, they were entered simultaneously
in a third block, with pro-environmental behaviors as the criterion variable.
Second, each form of television use found to be significant predictors of pro-environmental behaviors in
the path analyses were entered separately in a block after all other variables in each equation. The incremental R
2
statistic was used to formally test whether the various forms of media use retained a unique relationship with the
criterion variable beyond that which had already been established by the other variables in the equation.
Third, we used a stringent method for replication assessment outlined by Rosenthal (1991) to formally
cross-validate our results across the two data sets. Rosenthal argues against judging the success of a replication in a
dichotomous fashion based on the emergence of similar statistical significance levels. Instead, he contends that
researchers should make a final judgment concerning a replication’s success along a continuum and via a
comparison of the effects sizes. As noted by Jegerski (1991), “the abandonment of the p-value for comparing
replications is appropriate and long overdue” (p. 37). Accordingly, the tests for the incremental R
2
’s served as the
assessment tool for the merit of our replication (see Rosenthal [1984] for conversion equations).


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