JSM 2005 - Toronto

Abstract #304532

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 478
Type: Topic Contributed
Date/Time: Thursday, August 11, 2005 : 8:30 AM to 10:20 AM
Sponsor: Section on Survey Research Methods
Abstract - #304532
Title: Propensity Models versus Weighting Cell Approaches to Nonresponse Adjustment: A Methodological Comparison
Author(s): James Chromy*+ and Peter Siegel and Elizabeth Copello
Companies: RTI International and RTI International and RTI International
Address: 3040 Cornwallis Rd, RTP, NC, 27709, United States
Keywords: Nonresponse adjustment ; Generalized Exponential Model (GEM) ; weighting class ; propensity modeling ; raking
Abstract:

Statistical adjustment of nonresponse is a deep and pervasive issue for sample surveys. Contemporary statistical methods offer two broad classes of approach to nonresponse adjustment. One is the use of a traditional weighting cell approach. More recently, response propensity modeling, typically using logistic regression, has been developed as another approach to nonresponse adjustment. Additionally, RTIs General Exponential Model (GEM) is a generalization of weight adjustment methods; in addition to nonresponse adjustment, it can optionally include features such as poststratification and weight trimming. We compare the results of the weighting class method, raking, a logistic regression propensity model, and GEM, focusing not only on nonresponse adjustment but on extreme weight adjustment and poststratification. For the one-dimensional case, it can be shown that the three methods will produce the same results. For multiple control dimensions, marginal totals, variances, and weight distributions are compared. We also conduct a limited nonresponse bias analysis and examine the effects each method has on reducing nonresponse bias.

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Revised March 2005