Koffarnus Mikhail N, Franck Christopher T, Stein Jeffrey S, Bickel Warren K
Virginia Tech Carilion Research Institute, Virginia Tech.
Exp Clin Psychopharmacol. 2015 Dec;23(6):504-12. doi: 10.1037/pha0000045. Epub 2015 Aug 17.
Behavioral economic demand analyses that quantify the relationship between the consumption of a commodity and its price have proven useful in studying the reinforcing efficacy of many commodities, including drugs of abuse. An exponential equation proposed by Hursh and Silberberg (2008) has proven useful in quantifying the dissociable components of demand intensity and demand elasticity, but is limited as an analysis technique by the inability to correctly analyze consumption values of zero. We examined an exponentiated version of this equation that retains all the beneficial features of the original Hursh and Silberberg equation, but can accommodate consumption values of zero and improves its fit to the data. In Experiment 1, we compared the modified equation with the unmodified equation under different treatments of zero values in cigarette consumption data collected online from 272 participants. We found that the unmodified equation produces different results depending on how zeros are treated, while the exponentiated version incorporates zeros into the analysis, accounts for more variance, and is better able to estimate actual unconstrained consumption as reported by participants. In Experiment 2, we simulated 1,000 datasets with demand parameters known a priori and compared the equation fits. Results indicated that the exponentiated equation was better able to replicate the true values from which the test data were simulated. We conclude that an exponentiated version of the Hursh and Silberberg equation provides better fits to the data, is able to fit all consumption values including zero, and more accurately produces true parameter values.
行为经济学需求分析量化了商品消费与其价格之间的关系,已被证明在研究包括滥用药物在内的许多商品的强化效力方面很有用。赫什和西尔伯格(2008年)提出的指数方程已被证明在量化需求强度和需求弹性的可分离成分方面很有用,但作为一种分析技术,它受到无法正确分析零消费值的限制。我们研究了这个方程的指数形式,它保留了原始赫什和西尔伯格方程的所有有益特征,但可以处理零消费值并改善其对数据的拟合。在实验1中,我们在从272名参与者在线收集的香烟消费数据中,在对零值的不同处理下,将修改后的方程与未修改的方程进行了比较。我们发现,未修改的方程根据零值的处理方式会产生不同的结果,而指数形式将零值纳入分析,解释了更多的方差,并且更能估计参与者报告的实际无约束消费。在实验2中,我们模拟了1000个具有先验已知需求参数的数据集,并比较了方程拟合情况。结果表明,指数方程更能复制模拟测试数据的真实值。我们得出结论,赫什和西尔伯格方程的指数形式对数据的拟合更好,能够拟合包括零在内的所有消费值,并且更准确地产生真实参数值。