Regression Models for Categorical and Limited Dependent Variables pdf epub mobi txt 电子书下载 2025

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出版者:SAGE Publications, Inc

作者:J. Scott Long

出品人:

页数:328

译者:

出版时间:1997-1-9

价格:USD 112.00

装帧:Hardcover

isbn号码:9780803973749

丛书系列:

图书标签:

统计学
计量分析
statistics
美国
methodology
定量研究
定量
E

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A unified treatment of the most useful models for categorical and limited dependent variables (CLDVs) is provided in this book. Throughout, the links among the models are made explicit, and common methods of derivation, interpretation and testing are applied. In addition, the author explains how models relate to linear regression models whenever possible. After a review of the linear regression model and an introduction to maximum likelihood estimation, the book then: covers the logit and probit models for binary outcomes; reviews standard statistical tests associated with maximum likelihood estimation; and considers a variety of measures for assessing the fit of a model. J Scott Long also: extends the binary logit and probit models to ordered outcomes; presents the multinomial and conditioned logit models for nominal outcomes; considers models with censored and truncated dependent variables with a focus on the tobit model; describes models for sample selection bias; presents models for count outcomes by beginning with the Poisson regression model; and compares the models from earlier chapters, discussing the links between these models and others not discussed in the book.