Non-response biases in surveys of school children: the case of the English PISA samples
AbstractWe analyse response patterns to an important survey of school children, exploiting rich auxiliary information on respondentsâ€™ and non-respondentsâ€™ cognitive ability that is correlated both with response and the learning achievement that the survey aims to measure. The survey is the Programme for International Student Assessment (PISA), which sets response thresholds in an attempt to control data quality. We analyse the case of England for 2000 when response rates were deemed high enough by the PISA organisers to publish the results, and 2003, when response rates were a little lower and deemed of sufficient concern for the results not to be published. We construct weights that account for the pattern of non-response using two methods, propensity scores and the GREG estimator. There is clear evidence of biases, but there is no indication that the slightly higher response rates in 2000 were associated with higher quality data. This underlines the danger of using response rate thresholds as a guide to data quality.
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Bibliographic InfoPaper provided by Department of Quantitative Social Science - Institute of Education, University of London in its series DoQSS Working Papers with number 10-04.
Length: 37 pages
Date of creation: 03 2010
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Non-response; bias; school survey; data linkage; PISA;
Other versions of this item:
- Micklewright, John & Schnepf, Sylke V. & Skinner, Chris, 2010. "Non-Response Biases in Surveys of School Children: The Case of the English PISA Samples," IZA Discussion Papers 4789, Institute for the Study of Labor (IZA).
- C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
- I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
This paper has been announced in the following NEP Reports:
- NEP-ALL-2010-04-17 (All new papers)
- NEP-EDU-2010-04-17 (Education)
- NEP-URE-2010-04-17 (Urban & Real Estate Economics)
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