Instrumental Variable Estimation in Generalized Linear Measurement Error Models
作者:
JeffreyS. Buzas,
LeonardA. Stefanski,
期刊:
Journal of the American Statistical Association
(Taylor Available online 1996)
卷期:
Volume 91,
issue 435
页码: 999-1006
ISSN:0162-1459
年代: 1996
DOI:10.1080/01621459.1996.10476970
出版商: Taylor & Francis Group
关键词: Estimating equations;Functional model;Logistic regression;Structural model
数据来源: Taylor
摘要:
Instrumental variable estimation in generalized linear measurement error models are studied. For models with canonical link functions, unbiased estimating equations are derived. The maximum likelihood estimator for the normal theory, structural linear instrumental variable model is shown to be a solution to the estimating equations derived herein. Logistic regression is studied in detail. An example is given and a simulation study described for the logistic model based on the Framingham Heart Study data.
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