A comparison of best-worst scaling marginal and rank methods

被引：4

作者：

Cheng, Haotian ^{[1
]}

Feuz, Ryan ^{[2
]}

Lambert, Dayton M. ^{[3
]}

机构：

[1] Univ Arizona, Sch Nat Resources & Environm, Tucson, AZ 85721 USA

[2] Utah State Univ, Dept Appl Econ, Logan, UT USA

[3] Oklahoma State Univ, Dept Agr Econ, Stillwater, OK USA

来源：

APPLIED ECONOMICS LETTERS | 2024年 / 31卷 / 15期

关键词：

Best-worst scaling; Monte Carlo experiment; marginal method; rank methods; CHOICE DATA;

D O I：

10.1080/13504851.2023.2187019

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

This study compares the marginal and the rank methods for analysing best-worst scaling case 2 data using a simulated and an empirical example dataset. Simulation results suggest the rank method improves accuracy of estimates compared to the marginal method as measured by bias and mean square error. The rank method reduced bias on average by 48% across all coefficient estimates as compared to the marginal-CL method. Results from the empirical example align with those of the simulation and added robustness to the findings.

引用

页码：1379 / 1382

页数：4

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