Technical Reports : Time-to-Event Endpoints

 
 

The use of weighted logrank statistics in group sequential testing and non-proportional hazards

  1. Summary: Daniel Gillen’s Ph.D. dissertation (University of Washington Department of Biostatisitics, 2003) that investigates of a number of issues related to analyses in the setting of non-proportional hazards. Results from this dissertation were also reported in the Sequential Analysis 2005, Biometrics 2005, Statistics and Probability Letters 2007, and BEPress 2007 manuscripts listed below


Information growth in a family of weighted logrank statistics under repeated analyses.

  1. Summary: An investigation of the sequential use of weighted logrank statistics in nonproportional hazards.

  2. Ref: Gillen DL, Emerson SS, Sequential Analysis 24: 1-22 (2005).



A note on P-values under group sequential testing and nonproportional hazards.

  1. Summary: Comparison of orderings of the outcome space and their impact on P values under nonproportional hazards.

  2. Ref: Gillen DL, Emerson SS, Biometrics 61: 546-551 (2005).



Non-transitivity in a class of weighted logrank statistics under non-proportional hazards.

  1. Summary: A demonstration of the non-transitivity of weighted logrank statististics under nonproportional hazards.

  2. Ref: Gillen DL, Emerson SS, Statistics and Probability Letters 77: 123-130 (2007).



A random walk approach for quantifying uncertainty in group sequential survival trials.

  1. Summary: An approach for quantifying uncertainty in future treatment effects when monitoring survival in an RCT.

  2. Ref: Gillen DL, Computational Statistics and Data Analysis 53: 609-620 (2009).



Evaluating a group sequential design in the setting of non-proportional hazards.

  1. Summary: An approach to the design and evaluation of a group sequential survival trial that relies upon the use of pre-existing pilot data to construct alternatives under non-proportional hazards treatment effects.

  2. Ref: Gillen DL, Emerson SS, (BEPress) (2007)



Exploring the benefits of adaptive sequential designs in time-to-event endpoint settings.

  1. Summary: When using a time to event as a primary endpoint there are some features that might suggest an advantage to a more adaptive approach.

  2. Ref: Emerson SC, Rudser KD, Emerson SS, Statistics in Medicine (in press).

 


Technical Report Topics:


  1. •Probability models

  2. •General RCT methods

  3. •Noninferiority trials

  4. •Stopping rules

  5. •Adaptive methods

  6. •Implementation

  7. •Frequentist inference

  8. •Bayesian methods

  9. •Survival outcomes

  10. •Longitudinal outcomes

  11. •Medical diagnosis

  12. •Missing data

  13. •Software