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Improving the Estimation of the Odds Ratio in Sampling Surveys using Auxiliary Information

Goga, Camelia and Ruiz-Gazen, Anne (2019) Improving the Estimation of the Odds Ratio in Sampling Surveys using Auxiliary Information. TSE Working Paper, n. 19-1000, Toulouse

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The odds-ratio measure is widely used in Health and Social surveys where the aim is to compare the odds of a certain event between a population at risk and a population not at risk. It can be defined using logistic regression through an estimating equation that allows a generalization to continuous risk variable. Data from surveys need to be analyzed in a proper way by taking into account the survey weights. Because the odds-ratio is a complex parameter, the analyst has to circumvent some difficulties when estimating confidence intervals. The present paper suggests a nonparametric approach that can take advantage of some auxiliary information in order to improve on the precision of the odds-ratio estimator. The approach consists in B-spline modelling which can handle the nonlinear structure of the parameter in a exible way and is easy to implement. The variance estimation issue is solved through a linearization approach and confidence intervals are derived. Two small applications are discussed.

Item Type: Monograph (Working Paper)
Language: English
Date: March 2019
Place of Publication: Toulouse
Uncontrolled Keywords: B-spline functions, estimating equation, influence function, linearization, logistic regression, survey data
Divisions: TSE-R (Toulouse)
Institution: Université Toulouse 1 Capitole
Site: UT1
Date Deposited: 27 Mar 2019 09:11
Last Modified: 29 Jul 2020 13:33
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