Matthew McBee
Statistical Approaches to Causal Analysis
Statistical Approaches to Causal Analysis
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Excellent- More about Statistical Approaches to Causal Analysis
This book provides an accessible introduction to causal inference in quantitative research, featuring worked example datasets and guidance on selecting conditioning methods, applying the Rubins Causal Model, and utilizing techniques and designs to better synthesize and analyze data. It is part of The SAGE Quantitative Research Kit.
Format: Paperback / softback
Length: 264 pages
Publication date: 21 March 2022
Publisher: SAGE Publications Ltd
This comprehensive book offers a thorough and accessible introduction to causal inference in quantitative research. It provides a clear roadmap for conducting various statistical causal analyses, with detailed examples and datasets throughout. By guiding readers through the steps involved in these analyses, the book empowers them to apply these methods to their own research endeavors.
The book delves into essential topics such as selecting the most suitable conditioning method for data, employing the Rubins Causal Model to ensure accurate causation inferences, and utilizing techniques like propensity scores, instrumental variables analysis, and regression discontinuity designs to synthesize and analyze diverse types of data.
As part of The SAGE Quantitative Research Kit, this book equips readers with the knowledge and confidence they need to excel in their quantitative research journey. Whether you are a novice or an experienced researcher, this book is an invaluable resource for understanding and applying causal inference techniques to enhance your understanding of the underlying relationships in your data.
Weight: 472g
Dimension: 170 x 242 x 18 (mm)
ISBN-13: 9781526424730
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