| SEU_simulation_main_GAUSSIAN {RARfreq} | R Documentation |
Sequential Estimation-adjusted Urn Model with Simulated Data (Gaussian Responses)
Description
Allocates patients to one of treatments based on sequential estimation-adjusted urn model (SEU) with simulated data.
Usage
SEU_simulation_main_GAUSSIAN(n, nstart, mu, sd, urn_comp, nstop,
replication, group_allo, add_rule_index, add_rule,
add_rule_full, sig_level)
Arguments
n |
The number of patients. The default is 500. |
nstart |
Burn-in sample size of each arm. The default is n/20. |
mu |
A vector of mean response for each treatment arm (where the first element refers to the control arm). The length of mu should correspond to the number of arms. The default is mu = c(4.5,5). |
sd |
A vector of response standard deviations for each treatment arm. (where the first element refers to the control arm). The length of sd should correspond to the number of arms. The default is sd = c(1.32, 0.72). |
urn_comp |
A vector of current urn composition. The default is NULL, which indicates no ball in the urn. |
nstop |
A vector of stopping cap of sample size for each arm. The trial stops if at least one arm reaches the corresponding cap. The default is NULL, which means no cap. |
replication |
the number of replications of the simulation. The default is 100. |
group_allo |
A number or a vector of group size(s) for allocation. If a number is given, the allocation ratios will be updated for each batch of group_allo samples. If a vector is given, the allocation ratios will be updated sequentially in group according to the vector. Any value greater than n will be omitted. The default is group_allo=1, which is the same as group_allo = seq(nstart*length(p)+1,n). |
add_rule_index |
Supply a number of 1 or 2 indicting the addition rules to target allocation functions. 1 = the SEU model targeting Neyman allocation; 2 = the SEU model that assigns probability of 0.6+1/K to winner at each step. The default is 1. |
add_rule |
Supply a user-specified addition rules function of x.df and arms when add_rule_index is NULL. Default is NULL. (See SEU_GAUSSIAN_raw for details on x.df and arms.) |
add_rule_full |
Indicator of reference data for updating addition rule. If TRUE, the addition rule is updated by full observation at each group allocation. If FALSE,the addition rule is updated by each group observation. The default is TRUE. |
sig_level |
Significant level (one-sided). The default is 0.05. |
Details
'SEU_simulation_main_GAUSSIAN' can sample response and adaptively randomize subjects group by group.
Value
allocation_mean - Average of allocation in each arm based on 'replication' repeats.
allocation_sd - Standard deviation of allocation in each arm based on 'replication' repeats.
SS_mean - Average of sample size in each arm based on 'replication' repeats.
SS_sd - Standard deviation of sample size in each arm based on 'replication' repeats.
power_aov - Average power of ANOVA test.
power_oneside - Average power for each of the k-th arm to perform one-sided Welch T-test against H0: mu_1>mu_k without multiplicity adjustment.
mu_estimate_mean - Average of estimated response mean 'mu'.
sd_estimate_mean - Average of estimated response standard deviation 'sd'.
mu_estimate_sd - Standard deviation of estimated response mean 'mu'.
sd_estimate_sd - Standard deviation of estimated response standard deviation 'sd'.
Examples
## Default method
SEU_simulation_main_GAUSSIAN(
n = 50,
nstart = round(50 / 20),
mu = c(4.5,5),
sd = c(1.32,0.72),
urn_comp = c(0,0),
nstop=c(50,50),
replication = 5,
group_allo = 1,
add_rule_index = 1,
add_rule = NULL,
add_rule_full = TRUE,
sig_level = 0.05
)