RCT Average Operating Characteristics — avg_oc_wr_ne

Function for calculating the average operating characteristics of two RCT bayesian designs for early gating with respect to the sample size in the experimental group, the sample size in the control group and possible historical data.

avg_oc_wr_ne_rct(
  N_c,
  N_e,
  delta,
  delta_power,
  confidence,
  e_a = 0.5,
  e_b = 0.5,
  c_a = 0.5,
  c_b = 0.5,
  h_a = 0.5,
  h_b = 0.5,
  N_h = NULL,
  RR_h = NULL,
  w = NULL,
  alpha_c,
  beta_c,
  trues = seq(0, 1, 0.01),
  plot = T,
  coresnum = NULL,
  legend = T,
  legend.pos = "topleft"
)

Arguments

N_c	Sample Size in the control group. Can be either a single value or a vector, but needs to be the same length as N_e.
N_e	Sample Size in the experimental group. Can be either a single value or a vector, but needs to be the same length as N_c.
delta	Required superiority to make a "GO" decision. Corresponds to \(\delta\).
delta_power	Superiority, at which decision power will be evaluated. Corresponds to \(\bar{\delta}\).
confidence	Required confidence to make "GO" decision. Corresponds to \(\gamma\).
e_a	Alpha parameter of Beta Prior Distribution for the experimental response rate. Corresponds to \(\alpha_e\). Default is \(\frac{1}{2}\).
e_b	Beta parameter of Beta Prior Distribution for the experimental response rate. Corresponds to \(\beta_e\). Default is \(\frac{1}{2}\).
c_a	Alpha parameter of Beta Prior Distribution for the control response rate. Corresponds to \(\alpha_c\). Default is \(\frac{1}{2}\).
c_b	Beta parameter of Beta Prior Distribution for the control response rate. Corresponds to \(\beta_c\). Default is \(\frac{1}{2}\).
h_a	Alpha parameter of Beta Prior Distribution for the historical control response rate. Corresponds to \(\alpha_h\). Only needs to be specified, if RR_h, N_h and w are also specified. Default is \(\frac{1}{2}\).
h_b	Beta parameter of Beta Prior Distribution for the historical control response rate. Corresponds to \(\beta_h\). Only needs to be specified, if RR_h, N_h and w are also specified. Default is \(\frac{1}{2}\).
N_h	Historical control sample size. Corresponds to \(n_h\). If specified together with RR_h and w, function will use setting 4 from pdf.
RR_h	Historical control response rate. Corresponds to \(p_h\). If specified together with N_h and w, function will use setting 4 from pdf.
w	Level of dynmaic borrowing. Corresponds to \(w\).
alpha_c	Alpha parameter of Beta Distribution for the control response rate used to calculate average operating characteristics. Corresponds to \(\alpha_c\).
beta_c	Beta parameter of Beta Distribution for the control response rate used to calculate average operating characteristics. Corresponds to \(\beta_c\).
trues	Sequence of true control response rates and experimental response rates, at which the Probability to Go will be computed. Default is seq(0,1,0.01) to ensure continuous plots and accurate results.
plot	Plots yes or no. Default is TRUE.
coresnum	Number of cores used for parallel computing, in case N_e is a vector. Default is the number of total cores - 1.
legend	Logical; whether or not to include legend in plot. Default is TRUE.
legend.pos	Position of legend. Default is "topleft".

Value

Either a vector containing the average decision power and average alpha (if N_e has length 1) or a matrix containing the average decision power and average decision alpha (if N_e has length > 1), where every row corresponds to one value of N_e.

Examples


# Setting 3
avg_oc_wr_ne_rct(
N_c = 25, N_e = 25, delta = 0.08,
delta_power = 0.13, confidence = 0.6,
alpha_c = 15, beta_c = 13
)
#> Avg. Dec. Alpha Avg. Dec. Power 
#>            0.15            0.47 



# Setting 4
avg_oc_wr_ne_rct(
N_c = 25, N_e = 25, delta = 0.08,
delta_power = 0.13, confidence = 0.6,
alpha_c = 15, beta_c = 13,
RR_h = 0.5, N_h = 100, w = 0.3
)
#> Avg. Dec. Alpha Avg. Dec. Power 
#>            0.14            0.49