{"product_id":"experimental-and-quasi-experimental-designs-for-generalized-causal-inference-0395615569","title":"Diseños experimentales y cuasi experimentales para la inferencia causal generalizada","description":"\u003ch2\u003eWhat makes this book essential for experimental psychology research?\u003c\/h2\u003e\u003cp\u003eThis book is a fundamental reference for understanding experimental and quasi-experimental designs applied to causal inference. Written by William R. Shadish, Thomas D. Cook, and Donald T. Campbell, three authorities in research methodology, the work offers an exhaustive and rigorous treatment of methods that allow establishing causal relationships in contexts where random assignment is not always possible. Its conceptual depth and clarity on complex topics make it an essential text for researchers and advanced students.\u003c\/p\u003e\u003ch2\u003eBook content and approach\u003c\/h2\u003e\u003cp\u003eThe book focuses on the generalization of causal inference from experimental and quasi-experimental designs. Unlike basic introductions, this work assumes some prior knowledge and delves into the theoretical and practical foundations of each design. Aspects such as internal, external, construct, and statistical validity, as well as threats to each, are discussed. The approach is applied, with examples from various disciplines such as psychology, education, and public health. The authors integrate recent advances in the field, expanding the legacy of Campbell and Stanley's classic.\u003c\/p\u003e\u003ch2\u003eRelationship with previous works by Campbell and Stanley\u003c\/h2\u003e\u003cp\u003eThis book is considered the natural successor to Campbell and Stanley's \u003cem\u003eExperimental and Quasi-Experimental Designs for Research\u003c\/em\u003e. The authors update and expand the original concepts, incorporating methodological developments from recent decades. While the previous text laid the groundwork, this work delves into the logic of causal inference and offers more sophisticated tools for study design. It is not a simple update, but a complete reworking that maintains the critical and analytical spirit of its predecessors.\u003c\/p\u003e\u003ch2\u003eBook structure\u003c\/h2\u003e\u003cp\u003eThe book is organized into several sections covering everything from the fundamentals of causal inference to specific designs. It includes chapters on true experimental designs, quasi-experimental designs such as interrupted time series and regression discontinuity, as well as advanced topics such as external validity and generalization. Each chapter presents concrete examples and discusses the strengths and weaknesses of each approach. In addition, practical recommendations for implementing the designs in real research contexts are included.\u003c\/p\u003e\u003ch2\u003eWho is this book for?\u003c\/h2\u003e\u003cp\u003eIt is primarily intended for researchers, methodologists, and graduate students in social, behavioral, and health sciences. Its level of detail makes it suitable for advanced research methods courses and for professionals seeking a deep understanding of causal designs. Although it is not a manual for beginners, those with a solid foundation in statistics and experimental design will find it an invaluable source of knowledge. It requires dedication, but the reward is a comprehensive understanding of how to make solid causal inferences.\u003c\/p\u003e\u003ch2\u003eFrequently asked questions\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eIs this book suitable for those new to experimental research?\u003c\/strong\u003e It is not the most recommendable as a first approach. Prior knowledge of basic designs and inferential statistics is suggested. For an introduction, it may be useful to start with more elementary texts and then move on to this one.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eDoes it include practical examples and applications?\u003c\/strong\u003e Yes, the book presents numerous examples taken from real research, which facilitates the connection between theory and practice. The authors illustrate how to apply the concepts in different contexts.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eAre topics such as interrupted time series designs or regression discontinuity designs covered?\u003c\/strong\u003e Yes, these and other quasi-experimental designs are discussed in detail. The book dedicates specific chapters to each type of design, analyzing their strengths and limitations.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWho are the authors and what experience do they have?\u003c\/strong\u003e William R. Shadish, Thomas D. Cook, and Donald T. Campbell are renowned methodologists with decades of experience in experimental and quasi-experimental research. Their contributions have been fundamental to the development of causal inference methods in social sciences.\u003c\/p\u003e\u003cp\u003e\u003cem\u003eThis product is an academic book and does not constitute professional advice. Its content is intended for educational and research purposes.\u003c\/em\u003e\u003c\/p\u003e","brand":"Shadish, Cook \u0026 Campbell","offers":[{"title":"Default Title","offer_id":48753327833242,"sku":null,"price":180.63,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0761\/4831\/0170\/files\/81LniWVjaoL._SL1500.jpg?v=1784213862","url":"https:\/\/vitaminaspain.es\/es\/products\/experimental-and-quasi-experimental-designs-for-generalized-causal-inference-0395615569","provider":"vitaminaspain","version":"1.0","type":"link"}