Statistical Analysis with Missing Data

By Roderick J. A. Little, Donald B. Rubin. 1988

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Eric B. Laber
2. Daniel J. Lizotte
3. Susan M. Shortreed
4. Michael R. Kosorok
5. Susan A. Murphy
6. Ying‐Qi Zhao
7. Chao Yu
8. Joelle Pineau

Citations in the corpus

• Informing sequential clinical decision-making through reinforcement learning: an empirical study (2010, positive): “4.1 below, we apply multiple imputation (Little and Rubin 1987; Rubin 1996; Schafer 1999) to use all the available data (individuals with both complete and incomplete data) in order to reduce bias.”
• Hierarchical Mixtures of Experts and the EM Algorithm (1993, neutral): “…(Cheeseman, et al. 1988; Nowlan, 1990) and density estimation (Specht, 1991), as well as the statistics literature, in which applications include missing data problems (Little & Rubin, 1987), mixture density estimation (Redner & Walker, 1984), and factor analysis (Dempster, Laird, & Rubin, 1977).”