Hierarchical vs. Non-Nested Tests For Contrasting expectancy-Valence Models: Some Effects of Cognitive...

This study tests the appropriateness of multiplicative versus additive expectancy-valence models for 82 undergraduate students. Participants are grouped according to the model that best explains their motivational force decisions to exert effort in a series of differing hypothetical college courses. Two statistical tests are used for grouping participants: the traditional hierarchical test for contrasting nested regression models, and a more complex test for contrasting non-nested regression models. Arguments are offered in favor of the non-nested test. Force decisions are obtained from a within-subjects analysis. The grouping tests are applied between subjects. Discriminant analyses are then used to determine if four cognitive characteristics affected the choice of model. These characteristics are tolerance for ambiguity (TA), scholastic aptitude in mathematics (SATM), facility in mathematics required in major curriculum (FMR), and cognitive complexity (CC). It is hypothesized that participants who have higher TA, SATM, FMR, and CC process expectancy valence information multiplicatively while those who have lower values of these cognitive characteristics, process the information additively. The hypothesis is supported for FMR. No effect on choice of models is found for TA, SATM, or CC, while controlling for FMR; but univariate tests show multipliers to have higher TA and SATM than adders. Some implications and suggestions for future research are discussed.