cohere                package:titecrm                R Documentation

_C_o_h_e_r_e_n_c_e _o_f _T_w_o-_s_t_a_g_e _C_R_M

_D_e_s_c_r_i_p_t_i_o_n:

     Returns a message on the coherence status of a two-stage CRM
     design.

_U_s_a_g_e:

     cohere(prior, target, n, x0, method="bayes", scale=sqrt(1.34), detail=TRUE)

_A_r_g_u_m_e_n_t_s:

   prior: A vector of initial estimates of toxicity probabilities
          associated the doses.

  target: The target DLT rate.

       n: Sample size of the trial.

      x0: A vector of treatment sequence according to the initial
          design.  Must be of length 'n'.

  method: A character string to specify the method for parameter
          estimation.  The default method ``bayes'' estimates the model
          parameter by the posterior mean.  Estimation using ``mle'' is
          to be made available.

   scale: Standard deviation of the normal prior of the model
          parameter.  Default is sqrt(1.34).

  detail: If TRUE, details about incoherent escalations will be
          displayed.

_D_e_t_a_i_l_s:

     Dose-toxicity relationship is assumed as an empiric power model
     $a_i^{\exp(beta)}$ where $a_i$ is the initial estimate of toxicity
     probability of dose level i and the model parameter $beta$ has a
     normal prior with mean 0 and scale to be provided by users.

     A two-stage CRM is defined by two components.  First, an initial
     design sequence ('x0') for dose assignments before any DLT is
     seen. When a DLT is seen, dose assignment decisions are switched
     to the CRM.  See Cheung (2005) in the reference section.

_V_a_l_u_e:

     A string character giving a message on the coherence status of a
     two-stage CRM design.

_R_e_f_e_r_e_n_c_e_s:

     Cheung, Y. K. and Chappell, R. (2000). Sequential designs for
     phase I clinical trials with late-onset toxicities.  Biometrics
     56:1177-1182.

     Cheung, Y. K. (2005). Coherence principles in dose-finding
     studies. Biometrika 92:863-873.

_E_x_a_m_p_l_e_s:

     # Create a simple data set
     prior <- c(0.05,0.10,0.20,0.35,0.50,0.70)
     target <- 0.2
     n <- 24
     x0 <- c(rep(1,3),rep(2,3),rep(3,3),rep(4,3),rep(5,3),rep(6,9))
     # The above design is coherent
     foo <- cohere(prior,target,n,x0)
     print(foo)

     # The design is incoherent if a larger target DLT rate is used.
     target2 <- 0.3
     foo2 <- cohere(prior,target2,n,x0)

