The use of Gaussian quadrature for estimation in frailty proportional hazards models

  • Liu L
  • Huang X
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Although sample size calculations have become an important element in the design of research projects, such methods for studies involving current status data are scarce. Here, we propose a method for calculating power and sample size for studies using current status data. This method is based on a Weibull survival model for a two-group comparison. The Weibull model allows the investigator to specify a group difference in terms of a hazards ratio or a failure time ratio. We consider exponential, Weibull and uniformly distributed censoring distributions. We base our power calculations on a parametric approach with the Wald test because it is easy for medical investigators to conceptualize and specify the required input variables. As expected, studies with current status data have substantially less power than studies with the usual right-censored failure time data. Our simulation results demonstrate the merits of these proposed power calculations.

Author-supplied keywords

  • Dependent censoring
  • Frailty models
  • Shared random effects model
  • Survival analysis

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  • Lei Liu

  • Xuelin Huang

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