A Note on the Estimation of the Multinomial Logit Model With Random Effects

By Zhen Chen, Lynn Kuo. 2001

119 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Marketing, Transportation

View Paper: https://www.semanticscholar.org/paper/56660d25de58922d1c92fd9d93349931a006de76

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In Economics and Econometrics

1. P. C. Motel
2. J. Choumert
3. A. Rojo-Ramírez
4. J. Diéguez-Soto
5. Stefanie Muff
6. J. Fieberg
7. M. Manzaneque

In Marketing

1. A. Rojo-Ramírez
2. J. Diéguez-Soto
3. M. Manzaneque

In Transportation

1. A. Rojo-Ramírez
2. J. Diéguez-Soto
3. M. Manzaneque

Citations in the corpus

• Accounting for individual-specific variation in habitat-selection studies: Efficient estimation of mixed-effects models using Bayesian or frequentist computation (2018, background): “(Whitehead, 1980; McCullagh and Nelder, 1989; Baker, 1994; Chen and Kuo, 2001; Lu and Zeger, 2007), where αnt is the stratum-specific intercept of animal n at time point t.”
• Stacking up the ladder: A panel data analysis of Tanzanian household energy choices (2017, background): “In the case of cooking fuels, these 23 A general outline of random effects multinomial logit models can be found in Frees (2004, Ch.11.2) and Chen and Kuo (2001), whilst that of a fixed effects approach to multinomial logit models can be found in Pforr (2014). categories are 1=firewood and animal…”
• Technological Innovation Inputs, Outputs, and Performance (2016, methodology): “…between R&D intensity and CTI (Hypothesis 1) To estimate the probabilities of developing CTI, we used a panel multinomial logit model with a longitudinal data structure and random effects (Chen & Kuo, 2001) to control for unobserved heterogeneity or spurious dependence between individuals.”
• Scale dependency and functional response in moose habitat selection (2009, background): “The probability of use of habitat types can be considered as a multinomial distribution that can be modelled as a Poisson log-linear model with random effects, belonging to the class of generalised linear mixed models (Chen and Kuo 2001).”
• The repeated insertion model for rankings: Missing link between two subset choice models (2004, unknown): “For this and many other reasons, it comes as no surprise that the multi-disciplinary and multi-faceted literature on probabilistic choice has mostly focused on binary choice (i.e., two-alternative forced choice) data (e.g., Ahn, 1995; Atkinson, Wampold, Lowe, Matthews & Ahn, Baler & Gaul, 1999; Bock”