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Analyzing Exposure and Attention Variables in Media Effects Research
Unformatted Document Text:  Exposure and Attention 12 indirect (self-reports of media exposure combined with content analyses of these media) measures of exposure can not assume that they are measuring the same construct or that their results will generalize across measures. The second finding to emerge from these correlations is relevant to Evans’ criticism of multiplicative measures. The intercorrelations for the zero-mean variables and the raw variables are identical, with one exception. Correlations between the multiplicative exposure-attention measure and the individual exposure, attention and recognition measures change dramatically depending on whether the multiplicative variable is formed from raw variables or mean-centered variables. The decrease in the strength of the relation between the multiplicative measure and its components (i.e., exposure and attention) is not surprising. In fact, a primary reason for mean- centering predictors in a regression model is to reduce multicollinearity between the individual predictors and their interaction. However, what was not expected was the finding that the relation between the multiplicative measure and the recognition and recall measures also varied dramatically depending on whether the multiplicative measure was based on raw values or zeroed values. Specifically, when the multiplicative measure was formed from raw attention and exposure scores the relation between it and the memory measures was significant and stronger than it was when the multiplicative measure was formed from zeroed values. In contrast, exposure and attention were both significantly related to ad recall and ad recognition, regardless of how the variables were scaled. This is precisely the phenomenon that Evans (1991) described. Testing additive and multiplicative models of exposure and attention Four regression analyses were performed, with memory for cigarette advertising as the

Authors: Aloise-Young, Patricia. and Slater, Michael.
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Exposure and Attention
12

indirect (self-reports of media exposure combined with content analyses of these media)
measures of exposure can not assume that they are measuring the same construct or that their
results will generalize across measures.
The second finding to emerge from these correlations is relevant to Evans’ criticism of
multiplicative measures. The intercorrelations for the zero-mean variables and the raw variables
are identical, with one exception. Correlations between the multiplicative exposure-attention
measure and the individual exposure, attention and recognition measures change dramatically
depending on whether the multiplicative variable is formed from raw variables or mean-centered
variables. The decrease in the strength of the relation between the multiplicative measure and its
components (i.e., exposure and attention) is not surprising. In fact, a primary reason for mean-
centering predictors in a regression model is to reduce multicollinearity between the individual
predictors and their interaction.
However, what was not expected was the finding that the relation between the
multiplicative measure and the recognition and recall measures also varied dramatically
depending on whether the multiplicative measure was based on raw values or zeroed values.
Specifically, when the multiplicative measure was formed from raw attention and exposure
scores the relation between it and the memory measures was significant and stronger than it was
when the multiplicative measure was formed from zeroed values. In contrast, exposure and
attention were both significantly related to ad recall and ad recognition, regardless of how the
variables were scaled. This is precisely the phenomenon that Evans (1991) described.
Testing additive and multiplicative models of exposure and attention
Four regression analyses were performed, with memory for cigarette advertising as the


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