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Publicado por Sage Publications Ltd, GB, 2022
ISBN 10: 1526424738 ISBN 13: 9781526424730
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Añadir al carritoPaperback. Condición: New. 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.
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ISBN 10: 1526424738 ISBN 13: 9781526424730
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Añadir al carritoPaperback. Condición: new. Paperback. 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. A practical, up-to-date, step-by-step guidance on causal analysis; which features worked example datasets throughout to see methods in action. McBee clearly demonstrates techniques such as Rubin causal model, direct acyclic graphs and propensity score analysis. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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ISBN 10: 1526424738 ISBN 13: 9781526424730
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ISBN 10: 1526424738 ISBN 13: 9781526424730
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Añadir al carritoCondición: New. A practical, up-to-date, step-by-step guidance on causal analysis which features worked example datasets throughout to see methods in action. McBee clearly demonstrates techniques such as Rubin causal model, direct acyclic graphs and propensity score analy.
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Añadir al carritoTaschenbuch. Condición: Neu. Statistical Approaches to Causal Analysis | Matthew McBee | Taschenbuch | The SAGE Quantitative Research Kit | Kartoniert / Broschiert | Englisch | 2022 | SAGE Publications Ltd | EAN 9781526424730 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.
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Añadir al carritoPaperback. Condición: Brand New. 160 pages. 9.53x6.69x0.60 inches. In Stock.
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Publicado por SAGE Publications Ltd, London, 2022
ISBN 10: 1526424738 ISBN 13: 9781526424730
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Añadir al carritoPaperback. Condición: new. Paperback. 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. A practical, up-to-date, step-by-step guidance on causal analysis; which features worked example datasets throughout to see methods in action. McBee clearly demonstrates techniques such as Rubin causal model, direct acyclic graphs and propensity score analysis. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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ISBN 10: 1526424738 ISBN 13: 9781526424730
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Añadir al carritoPaperback. Condición: New. 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.
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Añadir al carritoPaperback. Condición: Brand New. 160 pages. 9.53x6.69x0.60 inches. In Stock. This item is printed on demand.
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Publicado por SAGE Publications Ltd Mrz 2022, 2022
ISBN 10: 1526424738 ISBN 13: 9781526424730
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 266 pp. Englisch.
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Añadir al carritoTaschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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.