A comparison of different methods to handle missing data in the context of propensity score analysis

Handling missing data in propensity score estimation in comparative effectiveness evaluations: a systematic review

(2018) Lucas Malla et al.   Journal of Comparative Effectiveness Research

Propensity score analysis with partially observed covariates: How should multiple imputation be used?

(2017) Clémence Leyrat et al.   STATISTICAL METHODS IN MEDICAL RESEARCH

Appropriate inclusion of interactions was needed to avoid bias in multiple imputation

(2016) Kate Tilling et al.   JOURNAL OF CLINICAL EPIDEMIOLOGY

Comments on propensity score matching following multiple imputation

(2016) BBL Penning de Vries et al.   STATISTICAL METHODS IN MEDICAL RESEARCH

The performance of different propensity score methods for estimating absolute effects of treatments on survival outcomes: A simulation study

(2016) Peter C Austin et al.   STATISTICAL METHODS IN MEDICAL RESEARCH

Multiple imputation for IPD meta-analysis: allowing for heterogeneity and studies with missing covariates

(2015) M. Quartagno et al.   STATISTICS IN MEDICINE

Graphical Representation of Missing Data Problems

(2015) Felix Thoemmes et al.   STRUCTURAL EQUATION MODELING-A MULTIDISCIPLINARY JOURNAL

The REporting of studies Conducted using Observational Routinely-collected health Data (RECORD) Statement

(2015) Eric I. Benchimol et al.   PLOS MEDICINE

Inverse Probability Weighting with Missing Predictors of Treatment Assignment or Missingness

(2014) Shaun Seaman et al.   COMMUNICATIONS IN STATISTICS-THEORY AND METHODS

Selecting an Appropriate Caliper Can Be Essential for Achieving Good Balance With Propensity Score Matching

(2013) Mark Lunt   AMERICAN JOURNAL OF EPIDEMIOLOGY

Missing covariate data in clinical research: when and when not to use the missing-indicator method for analysis

(2012) R. H. H. Groenwold et al.   CANADIAN MEDICAL ASSOCIATION JOURNAL

A comparison of two methods of estimating propensity scores after multiple imputation

(2012) Robin Mitra et al.   STATISTICAL METHODS IN MEDICAL RESEARCH

Multiple imputation by chained equations: what is it and how does it work?

(2011) Melissa J. Azur et al.   INTERNATIONAL JOURNAL OF METHODS IN PSYCHIATRIC RESEARCH

An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies

(2011) Peter C. Austin   MULTIVARIATE BEHAVIORAL RESEARCH

Propensity scores: From naïve enthusiasm to intuitive understanding

(2011) Elizabeth Williamson et al.   STATISTICAL METHODS IN MEDICAL RESEARCH

Unpredictable bias when using the missing indicator method or complete case analysis for missing confounder values: an empirical example

(2010) Mirjam J. Knol et al.   JOURNAL OF CLINICAL EPIDEMIOLOGY

Optimal caliper widths for propensity-score matching when estimating differences in means and differences in proportions in observational studies

(2010) Peter C. Austin   PHARMACEUTICAL STATISTICS

Bias and efficiency of multiple imputation compared with complete-case analysis for missing covariate values

(2010) Ian R. White et al.   STATISTICS IN MEDICINE

Multiple imputation using chained equations: Issues and guidance for practice

(2010) Ian R. White et al.   STATISTICS IN MEDICINE

The Relative Ability of Different Propensity Score Methods to Balance Measured Covariates Between Treated and Untreated Subjects in Observational Studies

(2009) Peter C. Austin   MEDICAL DECISION MAKING

Balance diagnostics for comparing the distribution of baseline covariates between treatment groups in propensity-score matched samples

(2009) Peter C. Austin   STATISTICS IN MEDICINE

The performance of different propensity-score methods for estimating relative risks

(2008) Peter C. Austin   JOURNAL OF CLINICAL EPIDEMIOLOGY

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

(2008) Alessandra Mattei   Statistical Methods and Applications

A critical appraisal of propensity-score matching in the medical literature between 1996 and 2003

(2007) Peter C. Austin   STATISTICS IN MEDICINE