Abstract #301972

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JSM 2003 Abstract #301972
Activity Number: 52
Type: Contributed
Date/Time: Sunday, August 3, 2003 : 4:00 PM to 5:50 PM
Sponsor: Section on Survey Research Methods
Abstract - #301972
Title: Fitting Nested Logit Models to Complex Survey Data
Author(s): Moshe Feder*+
Companies: Research Triangle Institute
Address: PO Box 12194, Research Triangle Park, NC, 27709-2194,
Keywords:
Abstract:

Nested logit (NL) models are used to model discrete random choice. These models have the advantage over multinomial logit models in that they do not suffer from the independence from irrelevant alternatives paradox. Both multinomial logit and sequential logit models are special cases of NL models. There are a few versions of these models in the literature. Some are derived from random utility models. We have fitted NL models to data from the National Household Survey on Drug Abuse (NHSDA) on choices of treatment. We first discuss our particular scenario and the derivation of our model from a random utility model. Complex survey data are characterized by clustering and unequal weighting. The estimation requires accounting for these characteristics, to avoid biases and incorrect standard errors. Although NL models are usually applied to data from complex surveys, past applications have ignored the survey design. We will discuss appropriate methods and provide results from both NHSDA and simulated data.

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