Statistical Models for the Social and Behavioral Sciences
Language: English
Published by Praeger Publishers, 1998
- Hardcover
- New
Condition: New
£ 91.15
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Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. The economic literature produced from multiple regression analysis requires a high level of mathematical sophistication to be understood. One of the key objectives of this book is to make the literature comprehensible to other disciplines - political scienc.
Seller Inventory # 446868056
- Title
- Statistical Models for the Social and Behavioral Sciences
- Author
- Crown, William H.
- Publisher
- Praeger Publishers
- Publication year
- 1998
- Condition
- New
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 0275953165
- ISBN 13
- 9780275953164
One of the key objectives of this book is to translate the results from the econometrics literature into language that policy analysts from other disciplines can understand easily. A second objective is to present a discussion of so-called limited-dependent variable models. One of the assumptions of the regression model is that the dependent variable is measured on an interval scale. But often the dependent variable of interest is discrete or categorical. Whether someone is in poverty or, whether they are working full-time, part-time, or out of the labor force, marital status—all are examples of categorical variables that might be of policy interest. Moreover, the growing availability of large-scale public use data sets containing information on individuals and families has heightened the relevance of categorical variables in policy analysis. The mathematical preparation required to understand procedures for estimating categorical models is, however, even more daunting than that for fully understanding and using the regression model. As with the theoretical development of the regression model, most presentations of categorical models, such as Logit and Probit, are to be found in econometric literature. Moreover, this literature offers little in the way of practical advice on how to estimate and interpret model results. This book is the first to present a detailed and accessible discussion of multiple regression and limited-dependent variable models in the context of policy analysis. As such it will be an invaluable resource for most scholars, researchers, and students in the social and behavioral sciences.
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