historical_binomial function

Historical data for binomial distribution

Wrapper function for historical data from binomial outcome.

historical_binomial(
  y0_treatment = NULL,
  N0_treatment = NULL,
  discount_function = "identity",
  y0_control = NULL,
  N0_control = NULL,
  alpha_max = 1,
  fix_alpha = FALSE,
  weibull_scale = 0.135,
  weibull_shape = 3,
  method = "fixed",
  .data = NULL
)

Arguments

• y0_treatment: scalar. Number of events for the historical treatment arm.

• N0_treatment: scalar. Number of observations of the historical treatment group.

• discount_function: character. If incorporating historical data, specify the discount function. Currently supports the Weibull function (discount_function="weibull"), the scaled-Weibull function (discount_function="scaledweibull"), and the identity function (discount_function="identity"). The scaled-Weibull discount function scales the output of the Weibull CDF to have a max value of 1. The identity discount function uses the posterior probability directly as the discount weight. Default value is "identity". See bdpnormal for more details.

• y0_control: scalar. Number of events for the historical control arm.

• N0_control: scalar. Number of observations of the historical control group.

• alpha_max: scalar. Maximum weight the discount function can apply. Default is 1. For a two-arm trial, users may specify a vector of two values where the first value is used to weight the historical treatment group and the second value is used to weight the historical control group.

• fix_alpha: logical. Fix alpha at alpha_max? Default value is FALSE.

• weibull_scale: scalar. Scale parameter of the Weibull discount function used to compute alpha, the weight parameter of the historical data. Default value is 0.135. For a two-arm trial, users may specify a vector of two values where the first value is used to estimate the weight of the historical treatment group and the second value is used to estimate the weight of the historical control group. Not used when discount_function = "identity".

• weibull_shape: scalar. Shape parameter of the Weibull discount function used to compute alpha, the weight parameter of the historical data. Default value is 3. For a two-arm trial, users may specify a vector of two values where the first value is used to estimate the weight of the historical treatment group and the second value is used to estimate the weight of the historical control group. Not used when discount_function = "identity".

• method: character. Analysis method with respect to estimation of the weight paramter alpha. Default method "mc" estimates alpha for each Monte Carlo iteration. Alternate value "fixed" estimates alpha once and holds it fixed throughout the analysis. See the the bdpsurvival vignette

  vignette("bdpsurvival-vignette", package="bayesDP") for more details.

• .data: NULL. stores the proportion of control and treatment, please do not fill it in.

Returns

a list with historical data for control and treatment group with the discount function.

Examples

historical_binomial(y0_treatment = 5, N0_treatment = 10, y0_control = 15, N0_control = 23)
historical_binomial(y0_treatment = 5, N0_treatment = 10, y0_control = 15, N0_control = 23,
                     discount_function = "weibull", alpha_max = 1, fix_alpha = FALSE,
                     weibull_scale = 0.135, weibull_shape = 3)