visit (version 2.2)

vtInterim: Conduct interim analysis

Description

Conduct an interim analysis for determining dose escalation actions

Usage

vtInterim(cur.obs.y, prev.obs.y = NULL, prev.res = NULL,
  etas = c(0.1, 0.3), dec.cut = 0.65, priors = NULL,
  prob.mdl = c("NONPARA", "NONPARA+", "PARA", "PARA+"), seed = NULL,
  ...)

Value

A class VTDEC list containing

• prob: Probabilities of each decision map region

• region: The region selected based on the sequential procedure described in visit

• ptox: Mean risk of DLT, \(E(p^{(l)})\)

• pres: Mean immune response rate, \(E(q^{(l)})\)

• con.prob: Conditional probabilities of each decision map region

• prev.res: Function parameter

• etas: Function parameter

• dec.cut: Function parameter

Arguments

cur.obs.y

Observed data from the current level, which is a vector of length 4. The numbers correspond to obs.y in vtPost.

prev.obs.y

Observed data from previous levels, which has the same structure as obs.y in vtPost.

prev.res

Response rate from the next lower dose level, say, \(l-1\). This can be a scalar representing the mean of the response rate \(E(q^{(l-1)})\), or a vector of posterior samples of the response rate \(q^{(l-1)}\). For \(l=1\), this value is set to \(0\).

etas

Vector of length 2 representing \((p_L, p_U)\). \(p_L\): lower bound of DLT risk, below which the current dose is considered absolutely safe; \(p_U\): upper bound of DLT risk above which the current dose is considered too toxic

dec.cut

Thresholds \(C_1,C_2,C_3\). If the vector length is shorter than \(3\), it is repeated to have \(3\) elements. See visit for details.

priors

A class VTPRIOR object created by vtPriorPar for PARA and PARA+ model.

prob.mdl

Option of the probability models:

• NONPARA+: non-parametric model

• PARA: partially parametric model

• PARA+: partially parametric+ model

Default value is NONPARA. See visit for details.

seed

Random seed

...

Additional arguments for vtPost

Details

Using data from previous levels and the current level to conduct Bayesian analysis, get the decision map information and make decision about dose escalation actions. The actions include stop the trial, escalate to the next higher dose level, or enroll more patients in the current level. See visit for details.

Examples

etas       <- c(0.1, 0.3)
dec.cut    <- c(0.6,0.6,0.6)
cur.obs.y  <- c(3, 2, 1, 1)
prev.obs.y <- c(5, 2, 0, 0)
rst.inter  <- vtInterim(cur.obs.y,  prev.obs.y = prev.obs.y,
                        prob.mdl = "NONPARA", etas = etas,
                        dec.cut = dec.cut,
                        nsmp = 2000);