|
Activity Number:
|
75
|
|
Type:
|
Contributed
|
|
Date/Time:
|
Sunday, August 6, 2006 : 4:00 PM to 5:50 PM
|
|
Sponsor:
|
Section on Nonparametric Statistics
|
| Abstract - #305540 |
|
Title:
|
Locally Efficient Estimators for Semiparametric Models with Measurement Error
|
|
Author(s):
|
Yanyuan Ma*+ and Raymond J. Carroll
|
|
Companies:
|
Texas A&M University and Texas A&M University
|
|
Address:
|
, College Station, TX, ,
|
|
Keywords:
|
semiparametric ; influence function ; efficiency ; measurement error ; backfitting
|
|
Abstract:
|
We derive constructive locally efficient estimators in semiparametric measurement error models. The setting is one where the likelihood function depends on variables measured with and without error, where the variables measured without error can be modeled nonparametrically. The algorithm is based on backfitting. We show that if one adopts a parametric model for the latent variable measured with error---and if this model is correct---then the estimator is semiparametric efficient; if the latent variable model is misspecified, our methods lead to a consistent and asymptotically normal estimator. Our method further produces an estimator of the nonparametric function that achieves the standard bias and variance property.
|
- The address information is for the authors that have a + after their name.
- Authors who are presenting talks have a * after their name.
Back to the full JSM 2006 program |
