Constructing bootstrap confidence intervals for principal component loadings in the presence of missing data: a multiple-imputation approach.

@article{Ginkel2011ConstructingBC,
  title={Constructing bootstrap confidence intervals for principal component loadings in the presence of missing data: a multiple-imputation approach.},
  author={Joost R van Ginkel and Henk A. L. Kiers},
  journal={The British journal of mathematical and statistical psychology},
  year={2011},
  volume={64 3},
  pages={498-515}
}
Earlier research has shown that bootstrap confidence intervals from principal component loadings give a good coverage of the population loadings. However, this only applies to complete data. When data are incomplete, missing data have to be handled before analysing the data. Multiple imputation may be used for this purpose. The question is how bootstrap confidence intervals for principal component loadings should be corrected for multiply imputed data. In this paper, several solutions are… CONTINUE READING

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