JSM 2015 Preliminary Program

Online Program Home
My Program

Abstract Details

Activity Number: 317
Type: Contributed
Date/Time: Tuesday, August 11, 2015 : 8:30 AM to 10:20 AM
Sponsor: SSC
Abstract #317458 View Presentation
Title: Simulation-Based Estimation in Generalized Linear Models with Categorical Response Variable and Mismeasured Covariates
Author(s): Rojiar Haddadian* and Yuliya Martsynyuk and Liqun Wang
Companies: University of Manitoba and University of Manitoba and University of Manitoba
Keywords: Measurement error ; Instrumental variable ; Method of moments ; generalized linear models ; Simulation- based estimation
Abstract:

We consider generalized linear models (GLM) that are widely used in medicine, social sciences, business applications, and other areas. For these models, real data analysis often brings in covariates that are measured with errors or not observed directly. Likelihood methods and moments based methods are the two main approaches for statistical estimation and inference in these models. The method of moments provides feasible alternatives to the likelihood approach when the likelihood function involves multiple integrals which do not have closed forms. This method does not require parametric assumptions for the distribution of the unobserved covariates and error components. We present a simulation-based method-of-moments approach for constructing estimators for unknown parameters of GLM's with categorical response variables and mismeasured covariates. We prove consistency and asymptotically normality of the obtained estimators under some regularity conditions, and illustrate our estimation approach through simulation studies.


Authors who are presenting talks have a * after their name.

Back to the full JSM 2015 program





For program information, contact the JSM Registration Department or phone (888) 231-3473.

For Professional Development information, contact the Education Department.

The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.

2015 JSM Online Program Home