Make assurance double sure: combination of two disclosure limitation methods and estimation of general regression models

DOI10.1007/s10182-008-0094-xzbMath1477.62368OpenAlexW3125772153MaRDI QIDQ2006867

Sandra Nolte, Anton Flossmann

Publication date: 12 October 2020

Published in: AStA. Advances in Statistical Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10182-008-0094-x

zbMATH Keywords

matchinginverse probability weightingmultiplicative measurement errorsimulation-extrapolationblankingdisclosure limitation technique

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Linear regression; mixed models (62J05) General nonlinear regression (62J02)

Cites Work

• Inverse probability weighted estimation for general missing data problems
• Estimation of multiplicative measurement-error models and some simulation results
• The central role of the propensity score in observational studies for causal effects
• Multiplicative Errors-in-Variables Models with Applications to Recent Data Released by the U.S. Department of Energy
• Semiparametric regression estimation in the presence of dependent censoring
• Matching As An Econometric Evaluation Estimator
• Inference and missing data
• Simulation-Extrapolation Estimation in Parametric Measurement Error Models
• A General Method for Dealing with Misclassification in Regression: The Misclassification SIMEX
• A Generalization of Sampling Without Replacement From a Finite Universe

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