Regression Models for Categorical and Limited Dependent Variables (Advanced Quantitative Techniques in the Social Sciences),Used

Regression Models for Categorical and Limited Dependent Variables (Advanced Quantitative Techniques in the Social Sciences),Used

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SKU: SONG0803973748
Brand: Sage Publications
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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.

⚠️ WARNING (California Proposition 65):

This product may contain chemicals known to the State of California to cause cancer, birth defects, or other reproductive harm.

For more information, please visit www.P65Warnings.ca.gov.

  • Q: What is the main focus of the book 'Regression Models for Categorical and Limited Dependent Variables'? A: The book provides a unified treatment of various models for categorical and limited dependent variables, emphasizing the connections among these models and their relation to linear regression.
  • Q: Who is the author of this book? A: The author of 'Regression Models for Categorical and Limited Dependent Variables' is John Scott Long.
  • Q: When was the book published? A: The book was published on January 9, 1997.
  • Q: What is the condition of the book? A: The book is listed as a 'Used Book in Good Condition'.
  • Q: How many pages does the book have? A: The book contains 327 pages.
  • Q: What type of binding does this book have? A: The book is bound in hardcover.
  • Q: What edition of the book is available? A: The available edition of the book is the first edition.
  • Q: What category does this book fall under? A: The book falls under the category of Probability & Statistics.
  • Q: What topics are covered in this book? A: The book covers models for categorical and limited dependent variables, along with methods of derivation, interpretation, and testing.
  • Q: Is this book suitable for beginners in statistics? A: While the book provides valuable insights into advanced quantitative techniques, it may be more suitable for readers with a foundational understanding of regression analysis.

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