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Jackknife Variance Estimation for Web Panel Health Survey Estimates Based on a Propensity-Score Meth

Abstract Number:

2921 

Submission Type:

Contributed Abstract 

Contributed Abstract Type:

Paper 

Participants:

Hee-Choon Shin (1)

Institutions:

(1) National Center for Health Statistics, N/A

First Author:

Hee-Choon Shin  
National Center for Health Statistics

Presenting Author:

Hee-Choon Shin  
National Center for Health Statistics

Abstract Text:

Taking advantage of web-based technology to develop and implement web surveys can be an efficient way of conducting surveys . The development of probability panels for administering web surveys has increased their usefulness. However, in addition to possible mode effects, differences remain between these and large national population surveys, which generally have lower sampling and non-sampling errors.
To improve the consistency of web survey estimates, it is common to adjust the estimates using a higher quality survey as the reference (benchmark) survey. One statistical method is a propensity score strategy. By concatenating the web survey and reference survey and applying a propensity score model to the combined data, the odds of being in the web survey is estimated by conditioning on selected covariates. For the variance estimation of adjusted estimates, typical Taylor-series or Jackknife variance estimators, based only on the web survey, underestimate the variance since the estimators ignore the variance components due to sampling variation in the reference survey.
To consider the sampling variation in the reference survey, we develop a Jackknife variance estimator for ad

Keywords:

Variance|Complex Sample|Jackknife| | |

Sponsors:

Survey Research Methods Section

Tracks:

Weighting/Variance Estimation

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