Robustness Tests for Quantitative Research (Paperback)

Eric Neumayer

ISBN 10: 1108401384 / ISBN 13: 9781108401388

Published by Cambridge University Press, Cambridge, 2017

About this Item

Paperback. The uncertainty that researchers face in specifying their estimation model threatens the validity of their inferences. In regression analyses of observational data, the 'true model' remains unknown, and researchers face a choice between plausible alternative specifications. Robustness testing allows researchers to explore the stability of their main estimates to plausible variations in model specifications. This highly accessible book presents the logic of robustness testing, provides an operational definition of robustness that can be applied in all quantitative research, and introduces readers to diverse types of robustness tests. Focusing on each dimension of model uncertainty in separate chapters, the authors provide a systematic overview of existing tests and develop many new ones. Whether it be uncertainty about the population or sample, measurement, the set of explanatory variables and their functional form, causal or temporal heterogeneity, or effect dynamics or spatial dependence, this book provides guidance and offers tests that researchers from across the social sciences can employ in their own research. Robustness testing allows researchers to explore the stability of estimates to alternative plausible model specifications. This book explains why robustness tests help researchers to deal with model uncertainty in quantitative research. With little technical knowledge required, it will be relevant to all social scientists as well as graduate students. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Seller Inventory # 9781108401388

Bibliographic Details

• Title: Robustness Tests for Quantitative Research (Paperback)
• Publisher: Cambridge University Press, Cambridge
• Publication Date: 2017
• Language: English
• ISBN 10: 1108401384
• ISBN 13: 9781108401388
• Binding: Paperback
• Condition: new

About this title

Synopsis

The uncertainty that researchers face in specifying their estimation model threatens the validity of their inferences. In regression analyses of observational data, the 'true model' remains unknown, and researchers face a choice between plausible alternative specifications. Robustness testing allows researchers to explore the stability of their main estimates to plausible variations in model specifications. This highly accessible book presents the logic of robustness testing, provides an operational definition of robustness that can be applied in all quantitative research, and introduces readers to diverse types of robustness tests. Focusing on each dimension of model uncertainty in separate chapters, the authors provide a systematic overview of existing tests and develop many new ones. Whether it be uncertainty about the population or sample, measurement, the set of explanatory variables and their functional form, causal or temporal heterogeneity, or effect dynamics or spatial dependence, this book provides guidance and offers tests that researchers from across the social sciences can employ in their own research.

About the Authors

Eric Neumayer is Professor of Environment and Development and Pro-Director Faculty Development at the London School of Economics and Political Science (LSE).

Thomas Plümper is Professor of Quantitative Social Research at the Vienna University of Economics and Business.