Randregret: A command for fitting random regret minimization models using Stata. (September 2021)

• Record Type: Journal Article
• Authors: Gutiérrez-Vargas, Álvaro A.; Meulders, Michel; Vandebroek, Martina
• Is Part Of: Stata journal. Volume 21:Number 3(2021)
• Page Start: 626
• Page End: 658
• Publication Date: 2021-09
• Subjects: st0649 -- randregret -- randregret_pure -- randregretpred -- discrete choice models -- semicompensatory behavior -- random utility maximization -- random regret minimization; Statistics -- Periodicals; Statistics -- Computer programs -- Periodicals; 001.422
• DOI: 10.1177/1536867X211045538
• Languages: English
• ISSNs: 1536-867X

Abstract

In this article, we describe therandregret command, which implements a variety of random regret minimization (RRM) models. The command allows the user to apply the classic RRM model introduced in Chorus (2010, European Journal of Transport and Infrastructure Research 10: 181–196), the generalized RRM model introduced in Chorus (2014, Transportation Research, Part B 68: 224–238), and also the µ RRM and pure RRM models, both introduced in van Cranenburgh, Guevara, and Chorus (2015, Transportation Research, Part A 74: 91–109). We illustrate the use of therandregret command by using stated choice data on route preferences. The command offers robust and cluster standarderror correction using analytical expressions of the score functions. It also offers likelihood-ratio tests that can be used to assess the relevance of a given model specification. Finally, users can obtain the predicted probabilities from each model by using therandregretpred command.