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

overviewR Documentation

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.