A package that uses Generalized Estimating Equations (GEE) to estimate Multivariate Accelerated Failure Time Model (AFT). This package implements recently developed inference procedures for AFT models with both the rank-based approach and the least squares approach. For the rank-based approach, the package allows various weight choices and uses an induced smoothing procedure that leads to much more efficient computation than the linear programming method. With the rank-based estimator as an initial value, the generalized estimating equation approach is used as an extension of the least squares approach to the multivariate case. Additional sampling weights are incorporated to handle missing data needed as in case-cohort studies or general sampling schemes.

References

Chiou, S., Kim, J. and Yan, J. (2014) Marginal Semiparametric Multivariate Accelerated Failure Time Model with Generalized Estimating Equation. Life Time Data, 20(4): 599--618.

Chiou, S., Kang, S. and Yan, J. (2014) Fast Accelerated Failure Time Modeling for Case-Cohort Data. Statistics and Computing, 24(4): 559--568.

Chiou, S., Kang, S. and Yan, J. (2014) Fitting Accelerated Failure Time Model in Routine Survival Analysis with R Package aftgee. Journal of Statistical Software, 61(11): 1--23.

Huang, Y. (2002) Calibration Regression of Censored Lifetime Medical Cost. Journal of American Statistical Association, 97, 318--327.

Jin, Z. and Lin, D. Y. and Ying, Z. (2006) On Least-squares Regression with Censored Data. Biometrika, 90, 341--353.

Johnson, L. M. and Strawderman, R. L. (2009) Induced Smoothing for the Semiparametric Accelerated Failure Time Model: Asymptotic and Extensions to Clustered Data. Biometrika, 96, 577 -- 590.

Zeng, D. and Lin, D. Y. (2008) Efficient Resampling Methods for Nonsmooth Estimating Functions. Biostatistics, 9, 355--363

Author

Maintainer: Sy Han Chiou schiou@utdallas.edu

Authors:

  • Sangwook Kang

  • Jun Yan