Participation,influence, and satisfaction in group decision making

The hypothesis that attitudinal effects of participation depend on individual differences in motivation was tested in a laboratory experiment with 56 three-man groups (leader and two members). Measures of the attractiveness of power and social acceptance were obtained prior to a group decision task, after which members described their perceived participation, influence, and satisfaction. Results showed that: (a) influence was more strongly related to satisfaction for members with strong, as opposed to weak, power motives; (b) for members with strong affiliation motives, participation was more strongly related to satisfaction than was influence. Relationships varied across satisfaction aspects. It was concluded that participation may be associated with favorable role attitudes through different motive-attainment mechanisms in the group decision-making process.     

An individual difference model for the multidimensional analysis of preference data

A model for the analysis of paired comparison data is presented which combines features of the BTL-model with features of the Unfolding model. The model is metric, mathematically tractable, and has an exact algebraic solution. Since it is multidimensional and allows for individual differences, it is thought to be more realistic for some choice situations than either the Thurstone model or the BTL-model. No claim is made that the present model will be appropriate for all conceivable choice situations. Rather, it is argued that the fact that it is explicitly falsifiable is a point in its favor.This work was supported by a grant of the United States Public Health Service (1 R03 MH19139 01 MSM) and a David Ross (XR) grant of the Purdue Research Foundation (PRF 2132), both of which are gratefully acknowledged. We also owe thanks to Dr. Terry Cooper, whose careful scrutiny of an earlier draft of this paper allowed us to reduce the number of errors from n to n-1.     

Some new results on factor indeterminacy

Some relations between maximum likelihood factor analysis and factor indeterminacy are discussed. Bounds are derived for the minimum average correlation between equivalent sets of correlated factors which depend on the latent roots of the factor intercorrelation matrix . Empirical examples are presented to illustrate some of the theory and indicate the extent to which it can be expected to be relevant in practice.