title: Estimating heterogeneity in the probabilities of enumeration for dual-system estimation.
abstract: "We show how conditional logistic regression can be used to estimate the probability of being enumerated in a census and apply the model to the 1990 Post-Enumeration Survey (PES) in the United States.... We discuss some special problems caused by the fact that the PES sample area is open to migration between the captures.  We also consider the effect of data errors in estimation.  We characterize hard-to-enumerate populations and give some tentative estimates of correlation bias."
authors.forename: J M
authors.initials: JM
authors.lastname: Alho
authors.forename: M H
authors.initials: MH
authors.lastname: Mulry
authors.forename: K
authors.initials: K
authors.lastname: Wurdeman
authors.forename: J
authors.initials: J
authors.lastname: Kim
mesh_terms: D000569:Americas; D015982:Bias; D019352:Censuses; D003625:Data Collection; D003710:Demography; D019049:Developed Countries; D004641:Emigration and Immigration; D009656:North America; D011153:Population; D011154:Population Characteristics; D011157:Population Dynamics; D012106:Research; D012107:Research Design; D012494:Sampling Studies; D013223:Statistics as Topic; D014481:United States
keywords: Americas; Bias; Census; Census Methods; Data Adjustment; Data Analysis; Data Quality; Demographic Factors; Developed Countries; Error Sources; Estimation Technics; Measurement; Migration; North America; Northern America; Population; Population Dynamics; Population Statistics; Research Methodology; Sampling Studies; Studies; Surveys; United States