Sensitivity Analysis for Pearson-Lawley Corrections in the Context of Nonignorable Missingness,

Abstract

We consider a model sensitivity problem of a dependent variable on several exogenous variables while the dependent variable has some missing data. Under certain assumptions on the model of selected sample and on the selection mechanism, a mixture model is derived and some statistical properties are discussed. This model gives a way to derive Pearson Lawley (PL) correction formula for the covariance matrix and leads to a modification when the missingness is not ignorable. A sensitivity analysis is then discussed for the PL method. Finally, this modified PL method is applied to a real data set from Project A of Office of Naval Research. The results show some difference from that of using Pearson-Lawley method or of using listwise deletion.

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Document Details

Document Type
Technical Report
Publication Date
Aug 29, 1994
Accession Number
ADA323222

Entities

People

  • Bengt Muthen
  • Guanghan Liu

Organizations

  • Johns Hopkins University

Tags

DTIC Thesaurus Topics

  • Coefficients
  • Covariance
  • Data Science
  • Data Sets
  • Education
  • Factor Analysis
  • Information Science
  • Military Research
  • Normality
  • Probability
  • Psychology
  • Random Variables
  • Regression Analysis
  • Research Facilities
  • Statistical Algorithms
  • Statistical Analysis
  • Statistical Inference

Fields of Study

  • Mathematics

Readers

  • Regression Analysis.