Statistical Models for Causal Analysis - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Statistical Models for Causal Analysis write by Robert D. Retherford. This book was released on 2011-02-01. Statistical Models for Causal Analysis available in PDF, EPUB and Kindle. Simplifies the treatment of statistical inference focusing on how to specify and interpret models in the context of testing causal theories. Simple bivariate regression, multiple regression, multiple classification analysis, path analysis, logit regression, multinomial logit regression and survival models are among the subjects covered. Features an appendix of computer programs (for major statistical packages) that are used to generate illustrative examples contained in the chapters.
Statistical Models and Causal Inference
Statistical Models and Causal Inference - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Statistical Models and Causal Inference write by David A. Freedman. This book was released on 2010. Statistical Models and Causal Inference available in PDF, EPUB and Kindle. David A. Freedman presents a definitive synthesis of his approach to statistical modeling and causal inference in the social sciences.
Causal Inference in Statistics
Causal Inference in Statistics - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Causal Inference in Statistics write by Judea Pearl. This book was released on 2016-01-25. Causal Inference in Statistics available in PDF, EPUB and Kindle. CAUSAL INFERENCE IN STATISTICS A Primer Causality is central to the understanding and use of data. Without an understanding of cause–effect relationships, we cannot use data to answer questions as basic as "Does this treatment harm or help patients?" But though hundreds of introductory texts are available on statistical methods of data analysis, until now, no beginner-level book has been written about the exploding arsenal of methods that can tease causal information from data. Causal Inference in Statistics fills that gap. Using simple examples and plain language, the book lays out how to define causal parameters; the assumptions necessary to estimate causal parameters in a variety of situations; how to express those assumptions mathematically; whether those assumptions have testable implications; how to predict the effects of interventions; and how to reason counterfactually. These are the foundational tools that any student of statistics needs to acquire in order to use statistical methods to answer causal questions of interest. This book is accessible to anyone with an interest in interpreting data, from undergraduates, professors, researchers, or to the interested layperson. Examples are drawn from a wide variety of fields, including medicine, public policy, and law; a brief introduction to probability and statistics is provided for the uninitiated; and each chapter comes with study questions to reinforce the readers understanding.
Statistical Approaches to Causal Analysis
Statistical Approaches to Causal Analysis - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Statistical Approaches to Causal Analysis write by Matthew McBee. This book was released on 2022-03-01. Statistical Approaches to Causal Analysis available in PDF, EPUB and Kindle. This book provides an up-to-date and accessible introduction to causal inference in quantitative research. Featuring worked example datasets throughout, it clearly outlines the steps involved in carrying out various types of statistical causal analysis. In turn, helping you apply these methods to your own research. It contains guidance on: Selecting the most appropriate conditioning method for your data. Applying the Rubin’s Causal Model to your analysis, a mathematical framework for understanding and ensuring accurate causation inferences. Utilising various techniques and designs, such as propensity scores, instrumental variables analysis, and regression discontinuity designs, to better synthesise and analyse different types of data. Part of The SAGE Quantitative Research Kit, this book will give you the know-how and confidence needed to succeed on your quantitative research journey.
Statistical Models
Statistical Models - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Statistical Models write by David A. Freedman. This book was released on 2009-04-27. Statistical Models available in PDF, EPUB and Kindle. This lively and engaging book explains the things you have to know in order to read empirical papers in the social and health sciences, as well as the techniques you need to build statistical models of your own. The discussion in the book is organized around published studies, as are many of the exercises. Relevant journal articles are reprinted at the back of the book. Freedman makes a thorough appraisal of the statistical methods in these papers and in a variety of other examples. He illustrates the principles of modelling, and the pitfalls. The discussion shows you how to think about the critical issues - including the connection (or lack of it) between the statistical models and the real phenomena. The book is written for advanced undergraduates and beginning graduate students in statistics, as well as students and professionals in the social and health sciences.
