Conditional Scores and Optimal Scores for Generalized Linear Measurement-Error Models.

Abstract

This paper studies estimation of the parameters of generalized linear models in canonical form when the explanatory vector is measured with independent normal error. For the functional case, i.e., when the explanatory vectors are fixed constants, unbiased score functions are obtained by conditioning on certain sufficient statistics. This work generalizes results obtained for logistic regression. In the case that the explanatory vectors are independent and identically distributed with unknown distribtuion, efficient score functions are obtained using the theory developed in Begun et al. (1983). Keywords: Conditional score function; Efficient score function; Functional model; Generalized linear model; Measurement error; Structural model.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Oct 01, 1985
Accession Number
ADA168533

Entities

People

  • Leonard A. Stefanski
  • Raymond J. Carroll

Organizations

  • University of North Carolina at Chapel Hill

Tags

DTIC Thesaurus Topics

  • Air Force
  • Data Science
  • Discriminant Analysis
  • Distribution Functions
  • Efficiency
  • Equations
  • Estimators
  • Information Science
  • Measurement
  • New York
  • Normal Distribution
  • North Carolina
  • Probability
  • Random Variables
  • Scientific Research
  • Sequences
  • Statistics

Fields of Study

  • Mathematics

Readers

  • Regression Analysis.
  • Statistical inference.