Abstract
Birnbaum and Mellers criticized the use of partial correlation and multiple regression by Moreland and Zajonc to argue for two effects of stimulus exposure on liking. The null hypothesis that one variable mediates the effect of the variable on the dependent variables was not tested by their analyses. In response, Moreland and Zajonc reanalyzed their data, using structural equations analysis, and replied that there is evidence to support their previous conclusions. However, the present article shows that the small residuals from the one-mediator model may be due to shared nonlinearity (correlated errors) in three of the dependent variables. This simpler interpretation achieves a better fit to the Moreland and Zajonc data than the two-mediator model they advocated. Since the null hypothesis of one mediator is still viable, the burden of proof rests on those who contend that there is more to the exposure effect than stimulus recognition. Moreland and Zajonc (1977) replicated the exposure effect, that is, the finding that stimuli that are presented with greater frequency will be rated more favorably. They also asked their subjects to rate their familiarity with the stimuli, and they found a significant partial correlation between liking and exposure frequency when rated familiarity was partialed out. This partial correlation (and related regression analyses) led them to conclude that there is an additional, independent effect of exposure frequency on liking that is not mediated by stimulus recognition. Birnbaum and Mellers (1979) questioned the use of partial correlation and regression in this argument. They pointed out that the null hypothesis that a single variable (e.g., recognition) mediates the effect of the variable on both dependent variables predicts that both partials should have the same sign as the original correlations. Only if the dependent variable measuring recognition is assumed to be perfectly correlated with the mediator does the regression analy
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