Use of instrumental variables in the presence of heterogeneity and self-selection: an application to treatments of breast cancer patients

Instrumental variable (IV) methods are widely used in the health economics literature to adjust for hidden selection biases in observational studies when estimating treatment effects. Less attention has been paid in the applied literature to the proper use of IVs if treatment effects are heterogeneo...

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Published in	Health economics Vol. 16; no. 11; pp. 1133 - 1157
Main Authors	Basu, Anirban, Heckman, James J., Navarro-Lozano, Salvador, Urzua, Sergio
Format	Journal Article
Language	English
Published	Chichester, UK John Wiley & Sons, Ltd 01.11.2007 Wiley Periodicals Inc
Series	Health Economics
Subjects	Aged Alternative approaches Beneficiaries Breast cancer Breast Neoplasms - economics Breast Neoplasms - therapy Cancer therapies Comparative analysis essential heterogeneity Female Health Care Costs - statistics & numerical data Health economics Heterogeneity Humans instrumental variables local instrumental variable method Mastectomy Mastectomy - economics Mastectomy, Segmental - economics Medical treatment Medicare Models, Statistical Newly diagnosed Observational studies Older women Outcome Assessment (Health Care) - methods Outcome Assessment (Health Care) - statistics & numerical data Parameter estimation Radiation Radiotherapy - economics Selection Bias self-selection Selfselection Studies Surgery Treatment United States United States
Online Access	Get full text
ISSN	1057-9230 1099-1050
DOI	10.1002/hec.1291

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Abstract	Instrumental variable (IV) methods are widely used in the health economics literature to adjust for hidden selection biases in observational studies when estimating treatment effects. Less attention has been paid in the applied literature to the proper use of IVs if treatment effects are heterogeneous across subjects and individuals select treatments based on expected idiosyncratic gains or losses from treatments. In this paper we compare conventional IV analysis with alternative approaches that use IVs to estimate treatment effects in models with response heterogeneity and self‐selection. Instead of interpreting IV estimates as the effect of treatment at an unknown margin of patients, we identify the marginal patients and we apply the method of local IVs to estimate the average treatment effect and the effect on the treated on 5‐year direct costs of breast‐conserving surgery and radiation therapy compared with mastectomy in breast cancer patients. We use a sample from the Outcomes and Preferences in Older Women, Nationwide Survey which is designed to be representative of all female Medicare beneficiaries (aged 67 or older) with newly diagnosed breast cancer between 1992 and 1994. Our results reveal some of the advantages and limitations of conventional and alternative IV methods in estimating mean treatment effect parameters. Copyright © 2007 John Wiley & Sons, Ltd.
AbstractList	Instrumental variable (IV) methods are widely used in the health economics literature to adjust for hidden selection biases in observational studies when estimating treatment effects. Less attention has been paid in the applied literature to the proper use of IVs if treatment effects are heterogeneous across subjects and individuals select treatments based on expected idiosyncratic gains or losses from treatments. In this paper we compare conventional IV analysis with alternative approaches that use IVs to estimate treatment effects in models with response heterogeneity and self-selection. Instead of interpreting IV estimates as the effect of treatment at an unknown margin of patients, we identify the marginal patients and we apply the method of local IVs to estimate the average treatment effect and the effect on the treated on 5-year direct costs of breast-conserving surgery and radiation therapy compared with mastectomy in breast cancer patients. We use a sample from the Outcomes and Preferences in Older Women, Nationwide Survey which is designed to be representative of all female Medicare beneficiaries (aged 67 or older) with newly diagnosed breast cancer between 1992 and 1994. Our results reveal some of the advantages and limitations of conventional and alternative IV methods in estimating mean treatment effect parameters.Instrumental variable (IV) methods are widely used in the health economics literature to adjust for hidden selection biases in observational studies when estimating treatment effects. Less attention has been paid in the applied literature to the proper use of IVs if treatment effects are heterogeneous across subjects and individuals select treatments based on expected idiosyncratic gains or losses from treatments. In this paper we compare conventional IV analysis with alternative approaches that use IVs to estimate treatment effects in models with response heterogeneity and self-selection. Instead of interpreting IV estimates as the effect of treatment at an unknown margin of patients, we identify the marginal patients and we apply the method of local IVs to estimate the average treatment effect and the effect on the treated on 5-year direct costs of breast-conserving surgery and radiation therapy compared with mastectomy in breast cancer patients. We use a sample from the Outcomes and Preferences in Older Women, Nationwide Survey which is designed to be representative of all female Medicare beneficiaries (aged 67 or older) with newly diagnosed breast cancer between 1992 and 1994. Our results reveal some of the advantages and limitations of conventional and alternative IV methods in estimating mean treatment effect parameters. Instrumental variable (IV) methods are widely used in the health economics literature to adjust for hidden selection biases in observational studies when estimating treatment effects. Less attention has been paid in the applied literature to the proper use of IVs if treatment effects are heterogeneous across subjects and individuals select treatments based on expected idiosyncratic gains or losses from treatments. In this paper we compare conventional IV analysis with alternative approaches that use IVs to estimate treatment effects in models with response heterogeneity and self-selection. Instead of interpreting IV estimates as the effect of treatment at an unknown margin of patients, we identify the marginal patients and we apply the method of local IVs to estimate the average treatment effect and the effect on the treated on 5-year direct costs of breast-conserving surgery and radiation therapy compared with mastectomy in breast cancer patients. We use a sample from the Outcomes and Preferences in Older Women, Nationwide Survey which is designed to be representative of all female Medicare beneficiaries (aged 67 or older) with newly diagnosed breast cancer between 1992 and 1994. Our results reveal some of the advantages and limitations of conventional and alternative IV methods in estimating mean treatment effect parameters. Instrumental variable (IV) methods are widely used in the health economics literature to adjust for hidden selection biases in observational studies when estimating treatment effects. Less attention has been paid in the applied literature to the proper use of IVs if treatment effects are heterogeneous across subjects and individuals select treatments based on expected idiosyncratic gains or losses from treatments. In this paper we compare conventional IV analysis with alternative approaches that use IVs to estimate treatment effects in models with response heterogeneity and self‐selection. Instead of interpreting IV estimates as the effect of treatment at an unknown margin of patients, we identify the marginal patients and we apply the method of local IVs to estimate the average treatment effect and the effect on the treated on 5‐year direct costs of breast‐conserving surgery and radiation therapy compared with mastectomy in breast cancer patients. We use a sample from the Outcomes and Preferences in Older Women, Nationwide Survey which is designed to be representative of all female Medicare beneficiaries (aged 67 or older) with newly diagnosed breast cancer between 1992 and 1994. Our results reveal some of the advantages and limitations of conventional and alternative IV methods in estimating mean treatment effect parameters. Copyright © 2007 John Wiley & Sons, Ltd. Instrumental variable (IV) methods are widely used in the health economics literature to adjust for hidden selection biases in observational studies when estimating treatment effects. Less attention has been paid in the applied literature to the proper use of IVs if treatment effects are heterogeneous across subjects and individuals select treatments based on expected idiosyncratic gains or losses from treatments. In this paper we compare conventional IV analysis with alternative approaches that use IVs to estimate treatment effects in models with response heterogeneity and self-selection. Instead of interpreting IV estimates as the effect of treatment at an unknown margin of patients, we identify the marginal patients and we apply the method of local IVs to estimate the average treatment effect and the effect on the treated on 5-year direct costs of breast-conserving surgery and radiation therapy compared with mastectomy in breast cancer patients. We use a sample from the Outcomes and Preferences in Older Women, Nationwide Survey which is designed to be representative of all female Medicare beneficiaries (aged 67 or older) with newly diagnosed breast cancer between 1992 and 1994. Our results reveal some of the advantages and limitations of conventional and alternative IV methods in estimating mean treatment effect parameters. [PUBLICATION ABSTRACT] Instrumental variable (IV) methods are widely used in the health economics literature to adjust for hidden selection biases in observational studies when estimating treatment effects. Less attention has been paid in the applied literature to the proper use of IVs if treatment effects are heterogeneous across subjects and individuals select treatments based on expected idiosyncratic gains or losses from treatments. In this paper we compare conventional IV analysis with alternative approaches that use IVs to estimate treatment effects in models with response heterogeneity and self-selection. Instead of interpreting IV estimates as the effect of treatment at an unknown margin of patients, we identify the marginal patients and we apply the method of local IVs to estimate the average treatment effect and the effect on the treated on 5-year direct costs of breast-conserving surgery and radiation therapy compared with mastectomy in breast cancer patients. We use a sample from the Outcomes and Preferences in Older Women, Nationwide Survey which is designed to be representative of all female Medicare beneficiaries (aged 67 or older) with newly diagnosed breast cancer between 1992 and 1994. Our results reveal some of the advantages and limitations of conventional and alternative IV methods in estimating mean treatment effect parameters. [Copyright 2007 John Wiley and Sons, Ltd.]
Author	Basu, Anirban Urzua, Sergio Heckman, James J. Navarro-Lozano, Salvador
Author_xml	– sequence: 1 givenname: Anirban surname: Basu fullname: Basu, Anirban email: abasu@medicine.bsd.uchicago.edu organization: Section of General Internal Medicine, Department of Medicine, University of Chicago, Chicago, IL, USA – sequence: 2 givenname: James J. surname: Heckman fullname: Heckman, James J. organization: Department of Economics, University of Chicago, Chicago, IL, USA – sequence: 3 givenname: Salvador surname: Navarro-Lozano fullname: Navarro-Lozano, Salvador organization: Department of Economics, University of Wisconsin-Madison, Madison, WI, USA – sequence: 4 givenname: Sergio surname: Urzua fullname: Urzua, Sergio organization: Department of Economics, Northwestern University, Chicago, IL, USA
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Snippet	Instrumental variable (IV) methods are widely used in the health economics literature to adjust for hidden selection biases in observational studies when...
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SubjectTerms	Aged Alternative approaches Beneficiaries Breast cancer Breast Neoplasms - economics Breast Neoplasms - therapy Cancer therapies Comparative analysis essential heterogeneity Female Health Care Costs - statistics & numerical data Health economics Heterogeneity Humans instrumental variables local instrumental variable method Mastectomy Mastectomy - economics Mastectomy, Segmental - economics Medical treatment Medicare Models, Statistical Newly diagnosed Observational studies Older women Outcome Assessment (Health Care) - methods Outcome Assessment (Health Care) - statistics & numerical data Parameter estimation Radiation Radiotherapy - economics Selection Bias self-selection Selfselection Studies Surgery Treatment United States
Title	Use of instrumental variables in the presence of heterogeneity and self-selection: an application to treatments of breast cancer patients
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