Bootstrapping measurement error in multilevel models

  • Goldstein, Harvey (Principal Investigator)

Project Details


It is well-known that measurement error in dependent or independent variables can lead to misleading inferences in regression-type applications (including multilevel modelling). There have been developments which enable the question to be dealt with in some situations, but these are not widely available and deal with only a proportion of the possible measurement error mechanisms. This project will develop a methodology based on bootstrap resampling which would enable simple treatment of a wide range of measurement error mechanisms. This project is taking place in conjunction with the development of MLwiN, and it is aimed to operationalise the results in future releases.
Effective start/end date1/01/001/11/00

Structured keywords

  • SoE Centre for Multilevel Modelling


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