Robustness Tests for Quantitative Research
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- Publisher:
- Cambridge University Press
- Publication date:
- 20 September 2017
- 11 August 2017
- ISBN:
- 9781108233590
- 9781108415392
- 9781108401388
- Dimensions:
- (228 x 152 mm)
- Weight & Pages:
- 0.55kg, 268 Pages
- Dimensions:
- (228 x 152 mm)
- Weight & Pages:
- 0.44kg, 268 Pages
- Subjects:
- Political Theory, Research Methods in Politics, Research Methods in Sociology and Criminology, Research Methods In Sociology and Criminology, Statistical Theory and Methods, Politics and International Relations, Research Methods In Politics, Sociology
You may already have access via personal or institutional login- Subjects:
- Political Theory, Research Methods in Politics, Research Methods in Sociology and Criminology, Research Methods In Sociology and Criminology, Statistical Theory and Methods, Politics and International Relations, Research Methods In Politics, Sociology
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Book description
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.
Reviews
'Neumayer and Plümper have made an impressive contribution to research methodology. Rich in innovation and insight, Robustness Tests for Quantitative Research shows social scientists the way forward for improving the quality of inference with observational data. A must-read!'
Harold D. Clarke - Ashbel Smith Professor, University of Texas, Dallas
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