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References

Logo influence.ME

  • Bates, D., Maechler, M., and Dai, B. (2008). lme4: Linear mixed-effects models using S4 classes. R package version 0.999375-28.
  • Belsley, D.A., Kuh, E. & Welsch, R.E. (1980). Regression Diagnostics. Identifying Influential Data and Source of Collinearity. Wiley.
  • Cook, R. D. (1977). Detection of influential observation in linear regression. Technometrics, 19(1):15–18.
  • Kreft, I. and De Leeuw, J. (1998). Introducing Multilevel Modelling. Sage Publications.
  • Langford, I. H. and Lewis, T. (1998). Outliers in multilevel data. Journal of the Royal Statistical Society: Series A (Statistics in Society), 161:121–160.
  • Meer, T. Van der, Te Grotenhuis, M. & Pelzer, B. Inluential cases in multi-level modeling. A methodological comment on ’National context, religiosity, and volunteering’ by Ruiter and De Graaf. Current status: Accepted for publication in the American Sociological Review.
  • Snijders, T.A. & Bosker, R.J. (1999). Multilevel Analysis, an introduction to basic and advanced multilevel modeling. Sage.

Welcome to Curving Normality

Curving Normality is an academic blog maintained by Rense Nieuwenhuis. He uses this blog to write about the social sciences in general, fascinating journal papers, useful data, interesting books, statistics using R. In addition, his personal academic activities are shared here, as well.