overview: Overview over the parameters used in the 'randomizeR' package

In randomizeR: Randomization for Clinical Trials

Overview over the parameters used in the randomizeR package

Description

This list of parameters yields a comprehensive overview of the parameters used in the randomizeR package.

Arguments

a	nonnegative parameter which controls the degree of randomness: For decreasing a the allocations become deterministic, while for increasing a the randomization procedure tends to complete randomization.
accrualTime	duration of the accrual period in a survival study.
add	integer representing the number of balls that are added to the urn in each step.
alpha	the significance level of the test in each simulation.
bc	vector which contains the lengths k_1,...,k_l of each block. This means that the vector bc will have one entry for each block.
b	numeric vector of length at most 2 specifying the weight(s) for the punishment of deviations from the target value.
cenRate	exponential censoring rate in a survival study.
cenTime	total duration of a survival study (maximum length of followup).
d	effect size.
df	degrees of freedom (i.a. N-2).
eta	numeric specifying the magnitude of selection bias.
file	A connection, or a character string naming the file to write to.
filledBlock	logical whether the last block should be filled or not.
FTI	final tolerated imbalance. This is the difference in number of patients of groups A and B that is permitted at the end of a trial. Usually this is set to zero.
groups	character vector of labels for the different treatments.
ini	integer representing the initial urn composition.
k	length of the block to be permuted. k should be divisible by the number of treatment arms.
K	number of treatment groups (e.g. K=2 if we compare one experimental against one control treatment).
lb	lower bound for the starting value of the poisson distribution.
lambda	vector of the exponential rate parameters in each treatment group.
method	method that is used to generate the (random) allocation sequence. It can take values PBR, RAR, HAD, PWR, EBC, BSD, CR, TBD, UD, and MP.
mti	maximum tolerated imbalance in patient numbers during the trial.
mu	vector of the expected responses of the treatment groups, should have length K (i.e. one entry for each treatment group).
N	integer for the total sample size of the trial.
name	name of a variable.
obj	object specifying the randomization procedure, see randPar or createParam.
object	any R object.
p	success probability of the biased coin (e.g. in Efron's Biased Coin Design).
pr	vector with patient responses, i.e. each patients resulting value after the treatment.
q	"cut-off" value in [0.5,1]. This is the ratio of patients up from which the experimenter imposes selection bias on the data.
r	numeric indicating the number of random sequences to be generated at random, or missing.
ratio	vector of length K. The total sample number N and all used block lengths (bc) have to be divisible by sum(ratio).
rb	block lengths of the blocks that can be selected equiprobable at random.
rho	nonnegative parameter which my be adjusted according to how strongly it is desired to balance the experiment. If rho = 1, we have Wei's urn design with alpha = 0. If rho = 0, we have complete randomization.
rsob	randomization sequence (of one block).
rs	randomization sequence (of all blocks).
S	matrix for the computation of the probabilities in the maximal procedure.
saltus	integer or missing specifying the patient index (i.e. position) of the step in case of step time trend.
seed	a single value, interpreted as an integer, that specifies the seed for the random number generation.
sigma	vector of the standard deviations in each treatment group, should have length K (i.e. one entry for each treatment group).
SLs	numeric vector of length at most 2 specifying the lower and/or upper specified border.
theta	factor of the time trend for further details see type.
type	character vector indicating which biasing strategy the experimenter is using (selection bias) and which other bias is present in the clinical trial (e.g. time trend). All biases included in the vector are combined (i.e. added up) to form the total bias. Possible values are "none" (if no bias occurs), "CS" (resp. "DS") (if the experimenter uses the convergence (resp. divergence) strategy to invoke selection bias), LinT for linear time trend, LogT for log-linear time trend, StepT for step time trend, SigT for sigmoid time trend, PWR for knowledge of all up to the first observation in each block, MTI the next observation after reaching the maximal tolerated imbalance is reached will be known to the physician.
TV	numeric specifying the optimal desired value called the target value.
ub	upper bound for the last value of the poisson distribution.
varEq	logical parameter for the t.test: Shall the variances be treated as equal (TRUE= t.test) or different (FALSE= Welch.test).
x	a variable x.
allocRatio	numerical vector that represents the allocation ratio for the different strata in a clinical trial
strata	numeric specifying the number of strata in a clinical trial
maxcombo	logical specifying if the maxcombo test is used
weights	numeric specifying the weights used for the test. Unless specified an unweighted test is conducted.

randomizeR documentation built on Sept. 19, 2023, 1:08 a.m.