title: Pseudoscore-based estimation from biased observations.
abstract: There are many practical situations where observation of the primary variable Y for individuals in a population is incomplete and depends on some auxiliary variables X that are potentially correlated with Y. We consider parameter estimation for the distribution of Y with the incomplete data, without specifying the underlying association between Y and X. The approach is based on a class of pseudoscore functions using available information of X. We demonstrate the consistency and asymptotic normality of the estimators and study their finite-sample properties in various situations via simulation. The methodology is illustrated by an example involving kindergarten readiness skills in children with sickle cell disease.
authors.affiliation: Department of Statistics and Actuarial Science, Simon Fraser University, Vancouver, BC V5A 1S6, Canada. joanh@stat.sfu.ca
authors.forename: X Joan
authors.initials: XJ
authors.lastname: Hu
authors.forename: R Jason
authors.initials: RJ
authors.lastname: Schroeder
authors.forename: Winfred C
authors.initials: WC
authors.lastname: Wang
authors.forename: James M
authors.initials: JM
authors.lastname: Boyett
mesh_terms: D000755:Anemia, Sickle Cell; D015982:Bias; D002675:Child, Preschool; D003627:Data Interpretation, Statistical; D006801:Humans; D015233:Models, Statistical; D014481:United States