Evaluating generalizability and parameter consistency in learning models

A new evaluation method is proposed for comparing learning models used for predicting decisions based on experience. The method is based on the generalization of models' predictions at the individual level. First, it evaluates the ability to make a priori predictions for decisions in new tasks using parameters from different tasks performed by an individual decision-maker. Second, it evaluates the consistency of parameters estimated in different tasks performed by the same person. We use this method to examine two rules for updating past experience with payoff feedback: The Delta rule, where only the chosen option is updated; and a Decay-Reinforcement rule, where additionally, non-chosen options are discounted. The results reveal that although the Decay-Reinforcement rule fits the data better, it has poor generality and parameter consistency at the individual level. The current method thus improves the ability to select models based on their correspondence to consistent characteristics within individual decision-makers.     

Testing for measurement equivalence of human values across online and paper-and-pencil surveys

The following study investigates the measurement equivalence of an online and paper-and-pencil (PAP) survey of human values. For this purpose, a total of 250 respondents completed the 21-item version of the Portrait Value Questionnaire either online (n = 125) or by PAP (n = 125). This questionnaire was developed by Schwartz (Advances in experimental social psychology, Academic Press, New York, 1992) and has been included in the European Social Survey since 2002 to test his theory of basic human values. Measurement invariance was tested via a multiple group confirmatory factor analysis. The assessment of invariance included the three levels of configural, metric, and scalar invariance, and the latent means of the values between both samples were compared. Results of this study show that the measurements are invariant at the three levels (configural, metric, and scalar), but there are latent mean differences between the values across the surveys. These differences may be partly explained by age and level of education differences between the two samples. Based on these findings we conclude that the methods of measurement are essentially invariant.     

On the optimal number of scale points in graded paired comparisons

In market research, it is common practice to measure individuals’ brand or product preference through graded paired comparisons (GPCs). One important decision concerns the (odd) number of scale points (e.g., five, seven, nine, or eleven) that has to be assigned to either brands or products in each pair. Using data from an experiment with 122 students, we assessed the extent to which GPCs with a higher number of scale points (requiring more cognitive effort) really outperform GPCs with a smaller number of scale points (requiring less cognitive effort). Our data analyses have shown that one may reduce the (odd) number of scale points from eleven to nine or seven, depending on what minor compromises one is willing to make. The detailed psychometric results presented in this paper are useful to applied researchers as they help them in making well-informed decisions on the number of scale points in a GPC task.     

Joint Employer Status in Triangular Employment Relationships

The article examines the question of who should be considered the legal employer in triangular employment relationships. It is argued that outsourcing of employer responsibilities to temporary work agencies is illegitimate with regard to long‐term employees and must be curtailed; further, that even in the case of short‐term (‘traditional’) employment through agencies, there is reason to place some employer responsibilities with the user firm. The suggested solution supports regulations directed at preventing agency employment abuse, as currently exist in some European countries, but at the same time would place employer responsibilities with both agency and user firm, jointly and severally.