Effects of the social dominance orientation on environmental attitudes of Chilean university students / Efectos de la orientación a la dominancia social sobre las actitudes ambientales de universitarios chilenos

By adopting a multidimensional approach to environmental attitudes (apathy, anthropocentrism, connectedness and emotional affinity with nature), this study explores the relationships between these dimensions, social dominance orientation (SDO) and political orientation. Two hundred and sixty-two Chilean university students filled out an ad hoc online questionnaire. Two confirmatory factorial analyses showed the four typologies of environmental attitudes and the two factors for SDO, which are labelled group dominance and opposition to equality. Through hierarchical regressions, group dominance showed higher explanatory power of environmental attitudes than political orientation. Furthermore, using the bootstrap procedure we showed that group dominance mediated between political orientation and attitudes of apathy, anthropocentrism and connectedness, while opposition to equality mediated between apathy and emotional affinity. We conclude that SDO is an important variable for measuring political ideology while also providing new nuances when analysing the relationships with environmental attitudes.     

The interpretation of maximum-likelihood estimation

Maximum-likelihood estimation is interpreted as a procedure for generating approximate pivotal quantities, that is, functions u(X;θ) of the data X and parameter θ that have distributions not involving θ. Further, these pivotals should be efficient in the sense of reproducing approximately the likelihood function of θ based on X, and they should be approximately linear in θ. To this end the effect of replacing θ by a parameter ϕ = ϕ(θ) is examined. The relationship of maximum-likelihood estimation interpreted in this way to conditional inference is discussed. Examples illustrating this use of maximum-likelihood estimation on small samples are given.     

Choice of the ridge factor from the correlation matrix determinant

Ridge regression is the alternative method to ordinary least squares, which is mostly applied when a multiple linear regression model presents a worrying degree of collinearity. A relevant topic in ridge regression is the selection of the ridge parameter, and different proposals have been presented in the scientific literature. Since the ridge estimator is biased, its estimation is normally based on the calculation of the mean square error (MSE) without considering (to the best of our knowledge) whether the proposed value for the ridge parameter really mitigates the collinearity. With this goal and different simulations, this paper proposes to estimate the ridge parameter from the determinant of the matrix of correlation of the data, which verifies that the variance inflation factor (VIF) is lower than the traditionally established threshold. The possible relation between the VIF and the determinant of the matrix of correlation is also analysed. Finally, the contribution is illustrated with three real examples.