Temporal Stochastic Inflation in Choice-Based Research
نویسندگان
چکیده
W examine the specification and interpretation of discrete-choice models used in behavioral theory testing, with a focus on separating “coefficient scale” from “error scale,” particularly over time. Numerous issues raised in the thoughtful commentaries of Louviere and Swait [Louviere, J., J. Swait. 2010. Discussion of “Alleviating the constant stochastic variance assumption in decision research: Theory, measurement, and experimental test.” Marketing Sci. 29(1) 18–22] and Hutchinson, Zauberman, and Meyer (HZM) [Hutchinson, J. W., G. Zauberman, R. Meyer. 2010. On the interpretation of temporal inflation parameters in stochastic models of judgment and choice. Marketing Sci. 29(1) 23–31] are addressed, specifically the roles of response scaling, preference covariates, actual versus hypothetical consumption, “immediacy,” and heterogeneity, as well as key differences between the experimental setup in Salisbury and Feinberg [Salisbury, L. C., F. M. Feinberg. 2010. Alleviating the constant stochastic variance assumption in decision research: Theory, measurement, and experimental test. Marketing Sci. 29(1) 1–17] and those typifying intertemporal choice and construal level theory. We strongly concur with most of the general conclusions put forth by the commentary authors, but we also emphasize a central point made in our research that may have been lost: that the temporal inflation effects observed in our empirical analysis could be attributed to stochastic effects, deterministic influences, or an amalgam; appropriate inferences depend on the nature of one’s data and stimuli. We also report on further analyses of our data, as well as a meta-analysis of HZM’s Table 1 that is consistent with our original findings. Implications for, and dimensions relevant to, future research on temporal stochastic inflation and its role in choice-based research are discussed.
منابع مشابه
Alleviating the Constant Stochastic Variance Assumption in Decision Research: Theory, Measurement, and Experimental Test
A often rely on methods that presume constant stochastic variance, even though its degree can differ markedly across experimental and field settings. This reliance can lead to misestimation of effect sizes or unjustified theoretical or behavioral inferences. Classic utility-based discrete-choice theory makes sharp, testable predictions about how observed choice patterns should change when stoch...
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T implications of Salisbury and Feinberg’s (2010) paper [Salisbury, L. C., F. M. Feinberg. 2010. Alleviating the constant stochastic variance assumption in decision research: Theory, measurement, and experimental test. Marketing Sci. 29(1) 1–17] for the process of model development and testing in the field of intertemporal choice analysis is explored. Although supporting the overall thrust of S...
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