What’s New in SAS/STAT 14.1


  • Allison, P. (2012). “Why You Probably Need More Imputations Than You Think.” Accessed February 20, 2015. http://www.statisticalhorizons.com/more-imputations.

  • Farrington, C. P. (2000). “Residuals for Proportional Hazards Models with Interval-Censored Survival Data.” Biometrics 56:473–482.

  • Forster, J. J., McDonald, J. W., and Smith, P. W. F. (2003). “Markov Chain Monte Carlo Exact Inference for Binomial and Multinomial Logistic Regression Models.” Statistics and Computing 13:169–177.

  • Fuller, W. A. (2009). Sampling Statistics. Hoboken, NJ: John Wiley & Sons.

  • Gray, R. J. (1988). “A Class of K-Sample Tests for Comparing the Cumulative Incidence of a Competing Risk.” Annals of Statistics 16:1141–1154.

  • Kenward, M. G., and Roger, J. H. (2009). “An Improved Approximation to the Precision of Fixed Effects from Restricted Maximum Likelihood.” Computational Statistics and Data Analysis 53:2583–2595.

  • Matsumoto, M., and Nishimura, T. (2002). “Mersenne Twister with Improved Initialization.” Accessed April 10, 2015. http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/MT2002/emt19937ar.html.

  • Pinheiro, J. C., and Chao, E. C. (2006). “Efficient Laplacian and Adaptive Gaussian Quadrature Algorithms for Multilevel Generalized Linear Mixed Models.” Journal of Computational and Graphical Statistics 15:58–81.

  • Rao, J. N. K., and Shao, J. (1992). “Jackknife Variance Estimation with Survey Data under Hot Deck Imputation.” Biometrika 79:811–822.

  • Rubin, D. B., and Schenker, N. (1986). “Multiple Imputation for Interval Estimation from Simple Random Samples with Ignorable Nonresponse.” Journal of the American Statistical Association 81:366–374.

  • Satorra, A., and Bentler, P. M. (1994). “Corrections to Test Statistics and Standard Errors in Covariance Structure Analysis.” In Latent Variables Analysis: Applications for Developmental Research, edited by A. von Eye, and C. C. Clogg, 399–419. Thousand Oaks, CA: Sage.

  • Van Buuren, S. (2012). Flexible Imputation of Missing Data. Boca Raton, FL: Chapman & Hall/CRC.

  • White, I. R., Daniel, R., and Royston, P. (2010). “Avoiding Bias Due to Perfect Prediction in Multiple Imputation of Incomplete Categorical Variables.” Computational Statistics and Data Analysis 54:2267–2275.

  • Wood, S. (2003). “Thin Plate Regression Splines.” Journal of the Royal Statistical Society, Series B 65:95–114.

  • Wood, S. (2006). Generalized Additive Models. Boca Raton, FL: Chapman & Hall/CRC.