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Activity Number: 139
Type: Contributed
Date/Time: Monday, August 5, 2013 : 8:30 AM to 10:20 AM
Sponsor: Survey Research Methods Section
Abstract - #308377
Title: Weighted Least Squares Estimation with Sampling Weights
Author(s): Hee-Choon Shin*+
Companies: National Center for Health Statistics
Keywords: Projection ; Regression ; Weighted Least Squares ; Weights

A set of unweighted normal equations assume that the response variable of each equation is equally reliable and should be treated equally. When there is a reason to expect higher reliability in response variable in some equations, we use weighted least squares (WLS) to give more weights to those equations. For an analysis of a survey data, sampling weights, as a relative importance variable, should be used for unbiased and efficient estimates. We will briefly go over the least squares theory and related issues, and propose a specific form of "weight" variable when we apply the sampling weights to the normal equations. The National Health and Nutrition Examination Survey (NHANES), a periodic survey conducted by the National Center for Health Statistics (NCHS), Centers for Disease Control and Prevention (CDC) will be analyzed to demonstrate the proposed approach.

Authors who are presenting talks have a * after their name.

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