Name: Interpreting Discrete Choice Models (Elements in Quantitative and Computational Methods for the Social Sciences) (en Inglés)
SKU: 54131635
Price: 39.83 USD
Availability: InStock
Author: Glasgow, Garrett
ISBN: 9781108819404

portada Interpreting Discrete Choice Models (Elements in Quantitative and Computational Methods for the Social Sciences) (en Inglés)

Interpreting Discrete Choice Models (Elements in Quantitative and Computational Methods for the Social Sciences) (en Inglés)

Formato

Libro Físico

Autor

Garrett Glasgow

Editorial

Cambridge University Press

Año

2022

Idioma

Inglés

N° páginas

Encuadernación

Tapa Blanda

Dimensiones

22.9x15.2x0.4 cm

Peso

0.12 kg.

ISBN13

9781108819404

Categorías

Ciencias políticas y teoría

Interpreting Discrete Choice Models (Elements in Quantitative and Computational Methods for the Social Sciences) (en Inglés)

Garrett Glasgow (Autor) · Cambridge University Press · Tapa Blanda

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Reseña del libro "Interpreting Discrete Choice Models (Elements in Quantitative and Computational Methods for the Social Sciences) (en Inglés)"

In discrete choice models the relationships between the independent variables and the choice probabilities are nonlinear, depending on both the value of the particular independent variable being interpreted and the values of the other independent variables. Thus, interpreting the magnitude of the effects (the "substantive effects") of the independent variables on choice behavior requires the use of additional interpretative techniques. Three common techniques for interpretation are described here: first differences, marginal effects and elasticities, and odds ratios. Concepts related to these techniques are also discussed, as well as methods to account for estimation uncertainty. Interpretation of binary logits, ordered logits, multinomial and conditional logits, and mixed discrete choice models such as mixed multinomial logits and random effects logits for panel data are covered in detail. The techniques discussed here are general, and can be applied to other models with discrete dependent variables which are not specifically described here.