Markov models with random effects for binary panel data

Ulf Böckenholt*

*Corresponding author for this work

Research output: Contribution to journalArticle

2 Scopus citations

Abstract

In the analysis of time-dependent choice data, it is important to take into account that individuals differ both in their preferences at a particular point in time and in the way they change their preferences over time. As a solution to this problem, this paper adopts Humphreys (1998) random-effects approach and combines the family of discrete-time, latent Markov models (Langeheine & van de Pol, 1990) with Thurstone's (1927) random utility framework. It is shown that the synthesis of both model classes yields a flexible and parsimonious framework for the analysis of time-stable preferences, systematic preference shifts, and structural dependencies between current and past preference states. Results from a simulation study and an application illustrate the feasibility and usefulness of random-effects Markovian models.

Original languageEnglish (US)
Pages (from-to)19-32
Number of pages14
JournalMPR-online
Volume7
StatePublished - Dec 1 2002

Keywords

  • Binary responses
  • Latent states
  • Mixed and latent Markov models

ASJC Scopus subject areas

  • Psychology(all)

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