Frequent Citations


In general, software used for statistical analysis does not need to be included in the list of references of a manuscript.  They are usually just referred to in the text.  For example, see these guidelines for how to refer to SAS in the text.  To cite R, use the following:

  • R Development Core Team.  (2011).  R: A Language and Environment for Statistical Computing.  R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0, URL

Statistical Methods

  • Huber, P. J. (1967).  The behavior of maximum likelihood estimates under nonstandard conditions.  In Proceedings of the fifth Berkeley symposium on mathematical statistics and probability, 221--233.
  • Liang K. Y. and Zeger, S. L.  (1986).  Longitudinal data analysis using generalized linear models.  Biometrika, 73(1):13--22.
  • Hastie, T., Tibshirani, R. and Friedman, J. H.  (2009).  The elements of statistical learning.  Springer-Verlag, New York.
  • Holm, S. (1979). A simple sequentially rejective multiple test procedure. Scandinavian Journal of Statistics, 6, 65–70.
  • Benjamini, Y., and Hochberg, Y. (1995). Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society Series B, 57, 289–300.
  • Benjamini, Y., and Yekutieli, D. (2001). The control of the false discovery rate in multiple testing under dependency. Annals of Statistics 29, 1165–1188.
  • Hommel, G. (1988). A stagewise rejective multiple test procedure based on a modified Bonferroni test. Biometrika, 75, 383–386.
  • Hochberg, Y. (1988). A sharper Bonferroni procedure for multiple tests of significance. Biometrika, 75, 800–803.
  • Shaffer, J. P. (1995). Multiple hypothesis testing. Annual Review of Psychology, 46, 561–576.
  • Wright, S. P. (1992). Adjusted P-values for simultaneous inference. Biometrics, 48, 1005–1013.
  • Breiman, L. and Friedman, J. and Stone, C. and Olshen, R. (1984).  Classification and regression trees.
  • Horvitz, D. G., and Thompson, D. J. (1952). A Generalization of Sampling Without Replacement From a Finite Universe. Journal of the American Statistical Association, 47, 663--685.
  • McCullagh, P. and Nelder, J. A. (1989).  Generalized Linear Models.
  • Tibshirani, R. (1996).  Regression shrinkage and selection via the lasso.  Journal of the Royal Statistical Society. Series B (Methodological), 58, 267--288.
  • Friedman, J., Hastie, T. and Tibshirani, R. (2010). Regularization Paths for Generalized Linear Models via Coordinate Descent.  Journal of Statistical Software, 33, 1--22.
  • Simon, N., Friedman, J., Hastie, T., Tibshirani, R. (2011). Regularization Paths for Cox's Proportional Hazards Model via Coordinate Descent, Journal of Statistical Software, 39, 1--13.
  • Newcombe, R. G. (1998).  Two-sided confidence intervals for the single proportion: comparison of seven methods, Statistics in medicine, 17, 857--872.
  • Newcombe, R. G. (1998).  Interval estimation for the difference between independent proportions: comparison of eleven methods, Statistics in medicine, 17, 873--890.