Maximum Likelihood with Auxiliary Information


Chambers, Ray and Wang, Suojin (2006) Maximum Likelihood with Auxiliary Information. Southampton, UK, Southampton Statistical Sciences Research Institute, 33pp. (S3RI Methodology Working Papers, (M06/08) ).

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Description/Abstract

Analysis of survey data does not happen in a vacuum. We typically know more about the target population than just the data observed in the survey. In some cases this extra information can be incorporated via calibration of survey weights. However, model fitting using weights often leads to increased standard errors. Also, weights are usually calibrated to a relatively small set of variables, while population data may be known for many more variables. Here we use the general approach to maximum likelihood estimation for complex surveys described in Breckling et al. (1994) to develop methods for efficiently incorporating external population information into model fitting using survey data. In particular, we focus on two simple, but very popular, models fitted to survey data. These are the linear regression model and the logistic regression model.

Item Type: Monograph (Working Paper)
Subjects: H Social Sciences > HA Statistics
Divisions: University Structure - Pre August 2011 > Southampton Statistical Sciences Research Institute
ePrint ID: 38977
Date Deposited: 14 Jun 2006
Last Modified: 27 Mar 2014 18:24
URI: http://eprints.soton.ac.uk/id/eprint/38977

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