Goodness-of-Fit Tests for Logistic Regression with Complex Survey Data

• Activity Number: 342
• Type: Contributed
• Date/Time: Tuesday, July 31, 2007 : 2:00 PM to 3:50 PM
• Sponsor: Section on Survey Research Methods
• Author(s): Amang S. Sukasih*+ and Donsig Jang and Haixia Xu
• Companies: Mathematica Policy Research, Inc. and Mathematica Policy Research, Inc. and Mathematica Policy Research, Inc.
• Keywords: unit nonresponse ; weighting adjustment ; response propensity ; logistic regression ; simulation

Abstract

The use of the logistic regression method for unit nonresponse weight adjustments has become common practice in recent years. With this method, users must go through the usual steps in regression modeling, including assessing the goodness-of-fit (GOF) of the model. However, a GOF test that accounts for the complex survey design is not readily available; or if it is, it is not always intuitive. This paper discusses the GOF test for logistic regression with complex survey data. We investigated how much bias the result is when the GOF test for a simple random sample data is applied to data from complex sample design, and whether there is an intuitive pattern in term of bias. We also developed a test that takes into account of the complex survey design. A simulation study was used to compare the simple-random-sample test and the proposed test with readily available GOF tests.