Robustness Tests Quantitative Research by Neumayer Eric (29 results)

PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.

Paperback. Condition: Like New. First Edition. In nearly new condition: bright, crisp and clean with no creases, just lightly rubbed. Looks and feels unread. Just a small publisher 'damaged' stamp at the prelims. Nonetheless not showing any defects. Thus a very nice copy, now offered for sale at a very reasonable price.

Condition: New. pp. 268.

Condition: New. pp. 268.

PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.

Condition: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

Condition: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

Condition: New. pp. 268.

Condition: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

Paperback. Condition: new. 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.

Condition: New. Brand New Original US Edition. Customer service! Satisfaction Guaranteed.

Condition: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.

Condition: New. Brand New Original US Edition. Customer service! Satisfaction Guaranteed.

Paperback. Condition: Brand New. 254 pages. 9.00x6.00x0.75 inches. In Stock.

Paperback / softback. Condition: New. New copy - Usually dispatched within 4 working days.

Hardcover. Condition: new. Hardcover. 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.

HRD. Condition: New. New Book. Shipped from UK. Established seller since 2000.

HRD. Condition: New. New Book. Shipped from UK. Established seller since 2000.

Paperback. Condition: New. Brand New ! Fast Delivery "International Edition " and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 4-6 Working days .and we do have flat rate for up to 2LB. Extra shipping charges will be requested This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.

Hardcover. Condition: Brand New. 254 pages. 9.00x6.00x0.40 inches. In Stock.

Paperback. Condition: new. 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 our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Hardback. Condition: New. New copy - Usually dispatched within 4 working days.

Kartoniert / Broschiert. Condition: New. 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 technica.

Paperback. Condition: new. 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 our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Taschenbuch. Condition: Neu. Neuware - This highly accessible book presents robustness testing as the methodology for conducting quantitative analyses in the presence of model uncertainty.

Hardcover. Condition: new. Hardcover. 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 our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Gebunden. Condition: New. 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 technica.

Hardcover. Condition: new. Hardcover. 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 our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Buch. Condition: Neu. Neuware - This highly accessible book presents robustness testing as the methodology for conducting quantitative analyses in the presence of model uncertainty.