Estimating and using propensity score in presence of missing background data: an application to assess the impact of childbearing on wellbeing

DOI10.1007/S10260-007-0086-0zbMath1405.62018OpenAlexW2148679658MaRDI QIDQ734471

Alessandra Mattei

Publication date: 13 October 2009

Published in: Statistical Methods and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10260-007-0086-0

zbMATH Keywords

missing dataignorabilitypropensity scorechildbearingwellbeing

Mathematics Subject Classification ID

Applications of statistics to social sciences (62P25) Sampling theory, sample surveys (62D05)

Related Items (4)

Propensity scores: From naïve enthusiasm to intuitive understanding ⋮ Inverse Probability Weighting with Missing Predictors of Treatment Assignment or Missingness ⋮ To Adjust or not to Adjust? Estimating the Average Treatment Effect in Randomized Experiments with Missing Covariates ⋮ Doubly robust treatment effect estimation with missing attributes

Uses Software

• Stata
• mvis
• pscore

Cites Work

• Affinely invariant matching methods with ellipsoidal distributions
• Multiple Imputation After 18+ Years
• The central role of the propensity score in observational studies for causal effects
• Matching As An Econometric Evaluation Estimator
• Characterizing the effect of matching using linear propensity score methods with normal distributions
• Inference and missing data
• Addressing complications of intention-to-treat analysis in the combined presence of all-or-none treatment-noncompliance and subsequent missing outcomes
• Matching Using Estimated Propensity Scores: Relating Theory to Practice

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