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Instrument Assisted Regression for Errors in Variables Models with Binary Response.

ABSTRACT: We study errors-in-variables problems when the response is binary and instrumental variables are available. We construct consistent estimators through taking advantage of the prediction relation between the unobservable variables and the instruments. The asymptotic properties of the new estimator are established, and illustrated through simulation studies. We also demonstrate that the method can be readily generalized to generalized linear models and beyond. The usefulness of the method is illustrated through a real data example.

SUBMITTER: Xu K

PROVIDER: S-EPMC4573640 | biostudies-literature | 2015 Mar

REPOSITORIES: biostudies-literature

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Instrument Assisted Regression for Errors in Variables Models with Binary Response.

Xu Kun K Ma Yanyuan Y Wang Liqun L

Scandinavian journal of statistics, theory and applications 20150301 1

We study errors-in-variables problems when the response is binary and instrumental variables are available. We construct consistent estimators through taking advantage of the prediction relation between the unobservable variables and the instruments. The asymptotic properties of the new estimator are established, and illustrated through simulation studies. We also demonstrate that the method can be readily generalized to generalized linear models and beyond. The usefulness of the method is illus ...[more]

PMID: 26392675

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