App Stats: Liublinska on "Addressing missing data issues in a study with rare binary outcomes constrained by a small sample size" 

 We hope you can join us this Wednesday, October 5, 2011 for the  Applied Statistics Workshop . Victoria Liublinska, a Ph.D. candidate from the  Statistics Department  at Harvard University, will present a paper entitled "Addressing missing data issues in a study with rare binary outcomes constrained by a small sample size". A light lunch will be served at 12 pm and the talk will begin at 12.15. 

 "Addressing missing data issues in a study with rare binary outcomes constrained by a small sample size" 
Victoria Liublinska (with D. Rubin and R. Gutman) 
Statistics Department, Harvard University 
CGIS K354 (1737 Cambridge St.)  
Wednesday, October 5th, 2011 12.00 pm 

 Abstract: 
 We (re)analyze the data obtained in a recent study conducted to evaluate safety and efficacy of a new device designed for vertebroplasty. The following are just a few issues that had to be addressed: missing data in some covariates, incorrect analysis applied initially to the primary endpoint, missing data in secondary endpoints. The latter involved additional challenges such as panel data (responses were collected twice over time with a non monotone missingness pattern), secondary endpoints were rare binary events. The analysis was complicated by a relatively small sample size. Our work demonstrates how a complex missing data issue can be broken down into a set of small tasks that are solved individually. Some tasks involved multivariate missing data imputation using chained equations (van Buuren and Oudshoorn 2000; Raghunathan et al. 2001) with carefully chosen conditional models. Other tasks called for new state-of-the-art solutions, such as  z-transformation procedure for combining repeated p-values (D. Rubin et al. 2011 (to be submitted), C. Licht 2009 Ph.D. thesis) or enhanced tipping-point graphs that assess sensitivity to various deviations from assumptions made about the missing data mechanism (Yan et al. 2009,  Campbell et al. 2011).