getinit {dfcrm}

Calibrating an initial design

Description

Returns an initial design that is compatible with the specified CRM setup when used in a two-stage design.

Usage

getinit(prior, target, n, nK = round(n/3), method = "bayes", 
    model = "empiric", intcpt = 3, scale = sqrt(1.34), detail = FALSE) 

Arguments

prior

A vector of initial guesses of toxicity probabilities associated the doses.

target

The target DLT rate.

n

The sample size of the trial.

nK

The minimum number of subjects required at the highest test dose in case of no toxicity throughout the trial.

method

A character string to specify the method for parameter estimation. The default method “bayes” estimates the model parameter by the posterior mean. Maximum likelihood estimation is specified by “mle”.

model

A character string to specify the working model used in the method. The default model is “empiric”. A one-parameter logistic model is specified by “logistic”.

intcpt

The intercept of the working logistic model. The default is 3. If model=“empiric”, this argument will be ignored.

scale

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

detail

If TRUE, intermediate designs will be displayed.

Details

An initial design will be incompatible to the CRM setup if the escalation pace is too conservative, i.e. slow. The algorithm in getinit starts the search of a compatible design with an aggressive initial design that starts a trial at the second highest dose. A more conservative design will be subsequently tested for compatibility if the current design is compatible. The sequence returned may be viewed as a conservative compatible initial design.

Value

A non-decreasing sequence of dose levels is returned.

References

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

Cheung, Y. K. (2011). Dose Finding by the Continual Reassessment Method. New York: Chapman & Hall/CRC Press.

See Also

cohere

Examples

prior <- c(0.05, 0.10, 0.20, 0.35, 0.50, 0.70)
target <- 0.2

# Seach stops because it requires at least 8 subjects at the highest dose
getinit(prior, target, 25, nK=8, method="mle", detail=TRUE)

# Search stops because an incompatible design is reached
getinit(prior, 0.3, 25, nK=8, method="mle", detail=TRUE)