Fellows Research Meetings

Using Paradata in Survey Data Analysis to Compensate for Measurement Error

Chris Skinner
London School of Economics and Political Science

There is growing interest among survey methodologists in collecting and using ‘paradata’, auxiliary variables related to the quality of the variables to be analysed. Paradata related to measurement error in some survey variable may be viewed as a kind of ‘accuracy indicator’, conveying the level of accuracy with which the survey variable is measured. This may be used in the design of the survey instrument. Here, the talk focusses on its use in survey data analysis to correct estimation for the potential biasing effects of measurement error.

Last reviewed: 7 September, 2017

Past Events

International Conference on Robust Statistics, July 2017