A marginal maximum likelihood method for the vector threshold model to analyze dichotomous choice data

Bibliographic Data

ID19276296
AuthorsHIROSHI HOJO (Tachikawa Hospital, corresponding author)
Year2003
Volume45
Issue3
Pages188-201
Publication date2003-09-01
Open AccessYes
TypeARTICLE
VenueJapanese Psychological Research (JOURNAL)
Journal identifiersISSN: 0021-5368 • E-ISSN: 1468-5884
PublisherWiley (PUBLISHER • GB)
DOI10.1111/1468-5884.t01-1-00044
OpenAlexW2152669418
LanguageEN
References cited12

At least two types of models, the vector model and the unfolding model can be used for the analysis of dichotomous choice data taken from, for example, the pick any/ n method. The previous vector threshold models have a difficulty with estimation of the nuisance parameters such as the individual vectors and thresholds. This paper proposes a new probabilistic vector threshold model, where, unlike the former vector models, the angle that defines an individual vector is a random variable, and where the marginal maximum likelihood estimation method using the expectation‐maximization algorithm is adopted to avoid incidental parameters. The paper also attempts to discuss which of the two models is more appropriate to account for dichotomous choice data. Two sets of dichotomous choice data are analyzed by the model

Econometrics · Expectation–maximization algorithm · Marginal likelihood · Mathematical optimization · Maximization · Maximum likelihood · Statistics · Threshold model · Variable (mathematics) · Applied Mathematics · Computer Science · Consumer Market Behavior and Pricing · Economic and Environmental Valuation · Mathematics · Spatial and Panel Data Analysis

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