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Design‐based analysis of embedded experiments with applications in the Dutch Labour Force Survey

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  • Jan A. Van Den Brakel

Abstract

Summary. Previous research has proposed a design‐based analysis procedure for experiments that are embedded in complex sampling designs in which the ultimate sampling units of an on‐going sample survey are randomized over different treatments according to completely randomized designs or randomized block designs. Design‐based Wald and t‐statistics are applied to test whether sample means that are observed under various survey implementations are significantly different. This approach is generalized to experimental designs in which clusters of sampling units are randomized over the different treatments. Furthermore, test statistics are derived to test differences between ratios of two sample estimates that are observed under alternative survey implementations. The methods are illustrated with a simulation study and real life applications of experiments that are embedded in the Dutch Labour Force Survey. The functionality of a software package that was developed to conduct these analyses is described.

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  • Jan A. Van Den Brakel, 2008. "Design‐based analysis of embedded experiments with applications in the Dutch Labour Force Survey," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(3), pages 581-613, June.
    • Handle: RePEc:bla:jorssa:v:171:y:2008:i:3:p:581-613
    DOI: 10.1111/j.1467-985X.2008.00532.x
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    Cited by:

    1. Buelens Bart & Van den Brakel Jan A., 2017. "Comparing Two Inferential Approaches to Handling Measurement Error in Mixed-Mode Surveys," Journal of Official Statistics, Sciendo, vol. 33(2), pages 513-531, June.
    2. Jan van den Brakel & Xichuan (Mark) Zhang & Siu‐Ming Tam, 2020. "Measuring Discontinuities in Time Series Obtained with Repeated Sample Surveys," International Statistical Review, International Statistical Institute, vol. 88(1), pages 155-175, April.
    3. James Chipperfield & Philip Bell, 2010. "Embedded experiments in repeated and overlapping surveys," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 173(1), pages 51-66, January.

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