Design-based analysis of factorial designs embedded in probability samples
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Jan A. van den Brakel1
Abstract
At national statistical institutes experiments embedded in ongoing sample surveys are frequently conducted, for example to test the effect of modifications in the survey process on the main parameter estimates of the survey, to quantify the effect of alternative survey implementations on these estimates, or to obtain insight into the various sources of non-sampling errors. A design-based analysis procedure for factorial completely randomized designs and factorial randomized block designs embedded in probability samples is proposed in this paper. Design-based Wald statistics are developed to test whether estimated population parameters, like means, totals and ratios of two population totals, that are observed under the different treatment combinations of the experiment are significantly different. The methods are illustrated with a real life application of an experiment embedded in the Dutch Labor Force Survey.
Key Words
completely randomized designs, design-based inference, embedded experiments, measurement error models, model-assisted inference, randomized block designs.
Table of content
2 Analysis of embedded K x L factorial experiments
3 Factorial designs with more than two factors
5 Testing new advance letters for the Dutch Labor Force Survey
1Department of Statistical Methods, Statistics Netherlands, P.O. Box 4481, 6401 CZ Heerlen, The Netherlands Department of Quantitative Economics, Maastricht University School of Business and Economics, P.O. Box 616, 6200 MD, Maastricht, The Netherlands, jbrl@cbs.nl
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