A concise, introductory text, Propensity Score Methods and Applications describes propensity score methods (PSM) and how they are used to balance the distributions of observed covariates between treatment conditions as a means to reduce selection bias. This new QASS title specifically focuses on the procedures of implementing PSM for research in social sciences, instead of merely demonstrating the effectiveness of the method.
Using succinct and approachable language to introduce the basic concepts of PSM, authors Haiyan Bai and M. H. Clark present basic concepts, assumptions, procedures, available software packages, and step-by-step examples for implementing PSM using real-world data, with exercises at the end of each chapter allowing readers to replicate examples on their own.
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Dr. Haiyan Bai is a Professor at the University of Central Florida. She earned her Ph.D. in quantitative research methodology at the University of Cincinnati. Her research interests include issues that revolve around statistical/quantitative methods, specifically, propensity score methods, resampling techniques, research design, measurement, and the application of statistical methods in social and behavioral sciences.
Dr. M. H. Clark is an Associate Lecturer, statistical consultant, and program evaluator at the University of Central Florida. She has a Ph.D. in Experimental Psychology with a specialization in research design and statistics from the University of Memphis. Her specific areas of expertise are in causal inference, selection bias in non-randomized experiments, and propensity score methods.
A concise, introductory text on propensity score methods that is easy to comprehend by those who have a limited background in statistics, and is practical enough for researchers to quickly generalize and apply the methods.
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Condición: Very Good. : Este libro explora los métodos de puntuación de propensión y sus aplicaciones en las ciencias sociales. Ofrece una guía concisa sobre cómo utilizar estos métodos cuantitativos para el análisis de datos y la investigación. Cubre los fundamentos teóricos y proporciona ejemplos prácticos para comprender y aplicar los métodos de puntuación de propensión de manera efectiva. EAN: 9781506378053 Tipo: Libros Categoría: Ciencias Título: Propensity Score Methods and Applications Autor: M. H. Clark| Haiyan Bai Idioma: en Páginas: 136 Formato: tapa blanda. Nº de ref. del artículo: Happ-2026-08-04-7e41673a
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Paperback. Condición: New. A concise, introductory text, Propensity Score Methods and Applications describes propensity score methods (PSM) and how they are used to balance the distributions of observed covariates between treatment conditions as a means to reduce selection bias. This new QASS title specifically focuses on the procedures of implementing PSM for research in social sciences, instead of merely demonstrating the effectiveness of the method. Using succinct and approachable language to introduce the basic concepts of PSM, authors Haiyan Bai and M. H. Clark present basic concepts, assumptions, procedures, available software packages, and step-by-step examples for implementing PSM using real-world data, with exercises at the end of each chapter allowing readers to replicate examples on their own. Nº de ref. del artículo: LU-9781506378053
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Condición: New. 2018. 1st Edition. Paperback. . . . . . Nº de ref. del artículo: V9781506378053
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Taschenbuch. Condición: Neu. Neuware - A concise, introductory text, Propensity Score Methods and Applications describes propensity score methods (PSM) and how they are used to balance the distributions of observed covariates between treatment conditions as a means to reduce selection bias. This new QASS title specifically focuses on the procedures of implementing PSM for research in social sciences, instead of merely demonstrating the effectiveness of the method. Using succinct and approachable language to introduce the basic concepts of PSM, authors Haiyan Bai and M. H. Clark present basic concepts, assumptions, procedures, available software packages, and step-by-step examples for implementing PSM using real-world data, with exercises at the end of each chapter allowing readers to replicate examples on their own. Nº de ref. del artículo: 9781506378053
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