Biased Estimation of Adjusted Odds Ratios From Incomplete Covariate Data Due to Violation of the Missing at Random Assumption

Vach, W. und Illi, S. (1996): Biased Estimation of Adjusted Odds Ratios From Incomplete Covariate Data Due to Violation of the Missing at Random Assumption. Sonderforschungsbereich 386, Discussion Paper 17

Abstract

We investigate the possible bias due to an erroneous missing at random assumption if adjusted odds ratios are estimated from incomplete covariate data using the maximum likelihood principle. A relation between complete case estimates and maximum likelihood estimates allows us to identify situations where the bias vanishes. Numerical computations demonstrate that the bias is most serious if the degree of the violation of the missing at random assumption depends on the value of the outcome variable or of the observed covariate. Implications for the analysis of prospective and retrospective studies are given.

• Dokumententyp: Paper
• Fakultät: Mathematik, Informatik und Statistik > Statistik > Sonderforschungsbereich 386 ; Sonderforschungsbereiche > Sonderforschungsbereich 386
• Themengebiete: 500 Naturwissenschaften und Mathematik > 510 Mathematik
• Sprache: Deutsch