crm_prior_beliefs {trialr}

Get the prior beliefs for a CRM trial scenario.

Description

Infer the prior beliefs consistent with the parameters and model form for a CRM dose-finding trial. This function could be interpreted as fitting the model to no data, thus examining the beliefs on dose-toxicity that are suggested by the parameter priors alone. This function provides the task analagous to stan_crm before any data has been collected.

Usage

crm_prior_beliefs(
  skeleton,
  target,
  model = c("empiric", "logistic", "logistic_gamma", "logistic2"),
  a0 = NULL,
  alpha_mean = NULL,
  alpha_sd = NULL,
  beta_mean = NULL,
  beta_sd = NULL,
  beta_shape = NULL,
  beta_inverse_scale = NULL,
  ...
)

Arguments

skeleton

a vector of the prior guesses of toxicity at doses. This should be a monotonically-increasing vector of numbers between 0 and 1.

target

the target toxicity probability, a number between 0 and 1. This value would normally be one of the values in skeleton, but that is not a requirement.

model

Character string to denote desired model. One of empiric, logistic, logistic_gamma, or logistic2. The choice of model determines which parameters are required. See Details.

a0

Value of fixed intercept parameter. Only required for certain models. See Details.

alpha_mean

Prior mean of intercept variable for normal prior. Only required for certain models. See Details.

alpha_sd

Prior standard deviation of intercept variable for normal prior. Only required for certain models. See Details.

beta_mean

Prior mean of gradient variable for normal prior. Only required for certain models. See Details.

beta_sd

Prior standard deviation of slope variable for normal prior. Only required for certain models. See Details.

beta_shape

Prior shape parameter of slope variable for gamma prior. Only required for certain models. See Details.

beta_inverse_scale

Prior inverse scale parameter of slope variable for gamma prior. Only required for certain models. See Details.

...

extra parameters passed to stan_crm.

Details

Different model choices require that different parameters are provided. See below.

Value

An object of class crm_fit

Parameter requirements of empiric model

• beta_sd

Parameter requirements of logistic model

• a0

• beta_mean

• beta_sd

Parameter requirements of logistic_gamma model

• a0

• beta_shape

• beta_inverse_scale

Parameter requirements of logistic2 model

• alpha_mean

• alpha_sd

• beta_mean

• beta_sd

Author(s)

Kristian Brock

References

O'Quigley, J., Pepe, M., & Fisher, L. (1990). Continual reassessment method: a practical design for phase 1 clinical trials in cancer. Biometrics, 46(1), 33-48. https://www.jstor.org/stable/2531628

Cheung, Y.K. (2011). Dose Finding by the Continual Reassessment Method. CRC Press. ISBN 9781420091519

See Also

stan_crm crm_fit

Examples

skeleton <- c(0.05, 0.1, 0.15, 0.33, 0.5)
target <- 0.33

prior_fit1 <- crm_prior_beliefs(skeleton, target, model = 'empiric',
                                beta_sd = sqrt(1.34))
prior_fit2 <- crm_prior_beliefs(skeleton, target, model = 'logistic_gamma',
                                a0 = 3, beta_shape = 1,
                                beta_inverse_scale = 2)