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A global logrank test for adaptive treatment strategies based on observational studies.

Publication ,  Journal Article
Li, Z; Valenstein, M; Pfeiffer, P; Ganoczy, D
Published in: Stat Med
February 28, 2014

In studying adaptive treatment strategies, a natural question that is of paramount interest is whether there is any significant difference among all possible treatment strategies. When the outcome variable of interest is time-to-event, we propose an inverse probability weighted logrank test for testing the equivalence of a fixed set of pre-specified adaptive treatment strategies based on data from an observational study. The weights take into account both the possible selection bias in an observational study and the fact that the same subject may be consistent with more than one treatment strategy. The asymptotic distribution of the weighted logrank statistic under the null hypothesis is obtained. We show that, in an observational study where the treatment selection probabilities need to be estimated, the estimation of these probabilities does not have an effect on the asymptotic distribution of the weighted logrank statistic, as long as the estimation of the parameters in the models for these probabilities is n-consistent. Finite sample performance of the test is assessed via a simulation study. We also show in the simulation that the test can be pretty robust to misspecification of the models for the probabilities of treatment selection. The method is applied to analyze data on antidepressant adherence time from an observational database maintained at the Department of Veterans Affairs' Serious Mental Illness Treatment Research and Evaluation Center.

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Published In

Stat Med

DOI

EISSN

1097-0258

Publication Date

February 28, 2014

Volume

33

Issue

5

Start / End Page

760 / 771

Location

England

Related Subject Headings

  • United States
  • Statistics & Probability
  • Research Design
  • Proportional Hazards Models
  • Probability
  • Patient Compliance
  • Observational Studies as Topic
  • Humans
  • Depression
  • Computer Simulation
 

Citation

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Li, Z., Valenstein, M., Pfeiffer, P., & Ganoczy, D. (2014). A global logrank test for adaptive treatment strategies based on observational studies. Stat Med, 33(5), 760–771. https://doi.org/10.1002/sim.5987
Li, Zhiguo, Marcia Valenstein, Paul Pfeiffer, and Dara Ganoczy. “A global logrank test for adaptive treatment strategies based on observational studies.Stat Med 33, no. 5 (February 28, 2014): 760–71. https://doi.org/10.1002/sim.5987.
Li Z, Valenstein M, Pfeiffer P, Ganoczy D. A global logrank test for adaptive treatment strategies based on observational studies. Stat Med. 2014 Feb 28;33(5):760–71.
Li, Zhiguo, et al. “A global logrank test for adaptive treatment strategies based on observational studies.Stat Med, vol. 33, no. 5, Feb. 2014, pp. 760–71. Pubmed, doi:10.1002/sim.5987.
Li Z, Valenstein M, Pfeiffer P, Ganoczy D. A global logrank test for adaptive treatment strategies based on observational studies. Stat Med. 2014 Feb 28;33(5):760–771.
Journal cover image

Published In

Stat Med

DOI

EISSN

1097-0258

Publication Date

February 28, 2014

Volume

33

Issue

5

Start / End Page

760 / 771

Location

England

Related Subject Headings

  • United States
  • Statistics & Probability
  • Research Design
  • Proportional Hazards Models
  • Probability
  • Patient Compliance
  • Observational Studies as Topic
  • Humans
  • Depression
  • Computer Simulation