Attribute-wise vs. alternative-wise mechanism in intertemporal choice: Testing the proportional difference, trade-off, and hyperbolic models.

Abstract

This study compared attribute- and alternative-wise mechanisms in intertemporal choice. The trade-off (Scholten, Read, & Sanborn, 2014) and the proportional difference models (González-Vallejo, 2002) were used to represent the attribute-wise mechanism. A stochastic version of the hyperbolic model based on Rachlin (2006) was adopted to represent the alternative-wise mechanism. Three experiments were performed. In Experiment 1, a typical intertemporal indifference choice task with a fixed delayed amount was used. In Experiment 2, a general choice task with nonimmediate delays and varied attribute values was employed. The magnitude effect was embedded in this experiment. In Experiment 3, the models were tested with option sets designed to induce subadditive and superadditive choice patterns (Scholten & Read, 2006, 2010). In Experiment 1, the hyperbolic model performed as well as the other models. In Experiments 2 and 3, the attribute-wise models outperformed the alternative-wise model in terms of fit, prediction, and handling of nonadditive patterns. The results support conclusions from recent studies (Dai & Busemeyer, 2014; Scholten et al., 2014), which suggest that attribute-wise mechanisms may be more suitable for describing intertemporal choices. Furthermore, the predictive performance was similar between the trade-off and the proportional difference (PD) models though the PD model is simpler.

From high- to one-dimensional dynamics of decision making: testing simplifications in attractor models

“…Though such decisions are inherently multi-attributive (time and value of the available options have to be weighted against each other), they have been modeled using models that accumulate a single evidence measure for the options available, be it simple sequential sampling models (Dai and Busemeyer 2014;Dai et al 2018;Zhao et al 2019) for the decision process within a trial, or more complex attractor models (Scherbaum et al 2016;Senftleben et al 2019b) for the decision process within and across trials. However, one might question, whether this simplification is valid (Amasino et al 2019;Cheng and González-Vallejo 2016;Dai et al 2018), especially when modeling complex decision patterns across trials with attractor models. Here, we test the validity of this assumption for the predictions from an attractor model.…”

The Relationship Between an Alternative Form of Cognitive Reflection Test and Intertemporal Choice

“…Intertemporal choice tasks. The intertemporal choice task employed in the present study was similar to those reported in some previous studies (Cheng & González-Vallejo, 2016;Scholten et al, 2014). The current study employed two conditions of intertemporal choice tasks with hypothetical gains and payments.…”

“…The present study aims to test the validity of CRT-2 by examining its correlation with intertemporal choice. To address the reliability issue, we employed an intertemporal choice task that was recently employed in other studies (Cheng & González-Vallejo, 2016;Dai & Busemeyer, 2014;Scholten, Read, & Sanborn, 2014). In this task, participants make repeated choices between a sooner, smaller reinforcer and a later, larger reinforcer.…”

Frontoparietal dynamics and value accumulation in intertemporal choice

“…The model we adopted assumed a trade-off mechanism between features of rewards and time delays in forming the representation of choice alternatives [19]. Previous studies have shown that such attribute-wise models could mimic various delay discounting curves in terms of subjective valuation [15] and that these models explain choice probabilities and response times as well or better than hyperbolic discounting models do [20][21][22]. Depending on specific experimental designs, attribute-wise models can provide more information on temporal dynamics when different attributes were presented sequentially (as in the current experimental design).…”