JSM 2005 Online Program

Abstract #303387

This is the preliminary program for the 2005 Joint Statistical Meetings in Minneapolis, Minnesota. Currently included in this program is the "technical" program, schedule of invited, topic contributed, regular contributed and poster sessions; Continuing Education courses (August 7-10, 2005); and Committee and Business Meetings. This on-line program will be updated frequently to reflect the most current revisions.

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Activity Number:	190
Type:	Contributed
Date/Time:	Monday, August 8, 2005 : 2:00 PM to 3:50 PM
Sponsor:	General Methodology
Abstract - #303387
Title:	Extension of Penalized Spline Propensity Prediction Method
Author(s):	Guangyu Zhang*+ and Roderick J. Little
Companies:	University of Michigan and University of Michigan
Address:	3566 Green Brier Blve, Ann Arbor, MI, 48105, United States
Keywords:	missing at random ; mean prediction ; spline ; propensity
Abstract:	Little and An (2004) developed a methodology for analysis of multivariate data with missing values. They proposed a penalized spline propensity prediction (SPP) method that yields robust model-based inference under the missing-at-random assumption. Propensity score for a missing variable is estimated and a regression model is fit with the spline of the propensity score as a covariate. The predicted marginal mean of the missing variable is consistent, but the SPP method does not yield a consistent estimate for other parameters, such as conditional means or regression coefficients. We extend this method to multivariate data with both continuous and categorical variables to yield consistent estimates of both marginal and conditional means. The extended SPP method is compared with the SPP method and simple alternatives in a simulation study.

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