Abstract #300659

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JSM 2003 Abstract #300659
Activity Number: 363
Type: Contributed
Date/Time: Wednesday, August 6, 2003 : 10:30 AM to 12:20 PM
Sponsor: Section on Survey Research Methods
Abstract - #300659
Title: An Application of the Bootstrap Variance Estimation Method to the Participation and Activity Limitation Survey
Author(s): Eric R. Langlet*+ and Dany Faucher and Eric Lesage
Companies: Statistics Canada and Statistics Canada and Insee
Address: R.H. Coats Bldg. 15R, Ottawa, ON, K1A 0T6, Canada
Keywords: bootsrap method ; without replacement design ; response propensity model ; logistic regression
Abstract:

The bootstrap method is increasingly used to estimate the variance of estimates obtained from complex survey designs. This method offers the advantage of being applicable to virtually any type of estimates. Also, the use of bootstrap weights in microdata files eliminates the need of keeping strata and Primary Sampling Units (PSUs) identifiers, reducing the risk of disclosure. The sampling plan of the Participation and Activity Limitations Survey (PALS) is a stratified two-stage design in which PSU's are selected without replacement with probability proportional to size. The survey presents specific challenges to the use of the bootstrap method. For instance, the sampling fraction for PALS is relatively high in many strata, which causes the bootstrap method to overestimate the variance. Results indicate that the size of this overestimation is small, however. Also, a logistic regression response propensity model is used for the nonresponse adjustment in PALS. It will be seen that a logistic regression model does not need to be fitted on each bootstrap sample for the nonresponse adjustment. This paper will address these issues as well as other particular problems.

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