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Analysis of Observational Health Care Data Using SAS by Andrew C. Leon, Josep Maria Haro, Robert Obenchain, Douglas E. Faries

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Chapter 5

Propensity Scoring with Missing Values

Yongming QuIlya Lipkovich

Abstract

5.1 Introduction

5.2 Data Example

5.3 Using SAS for IPW Estimation with Missing Values

5.4 Sensitivity Analyses

5.5 Discussion

References

 

Abstract

Propensity scores have been used widely as a bias reduction method to estimate the treatment effect in nonrandomized studies. Because many covariates are generally included in the model for estimating propensity scores, the proportion of subjects with at least one missing covariate can be relatively large. In this chapter, we review existing methods for estimating propensity scores when missing values are present. The methods include a complete covariate (CC) method, an indicator variable (IND) method, various multiple ...

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