Assessment criteria for clinical trials
Summarizes the criteria for the assessment of randomization procedures.
Randomization in clinical trials is supposed to control certain properties in clinical trials. In the randomizeR package, these properties are called issues
. It is crucial to decide which of the issues is relevant in the present clinical trial, because a randomization procedure that manages well one issue might behave very badly for another. The issues include
Selection bias
can occur if future treatment allocations are predictable due to restricted randomization and unmasking of past treatment assignments. The influence of selection bias on the test decision is represented by the selBias
class. The measure for the predictability of a randomization procedure is implemented in the corGuess
class representing the expected number of correct guesses.
Chronological bias
can occur if a time trend is present in the data. Time trends occur due to learning curves, relaxed inclusion/ exclusion criteria or new co-medication. Chronological bias is represented by the chronBias
class.
Additive combination of chronological and selection bias
may occur if a time trend and selection bias are present in the data. The combined bias is represented by the combineBias
class.
Balance
is important in order to ensure proper power estimation properties of the treatments. However, a high degree of balance favors selection bias. Depending on the clinical context, a randomization procedure should be chosen that admits a suitable imbalance. Imbalance bias is represented by the imbal
class. The power loss due to imbalance can be assessed directly via the setPower
class
Representation of randomization procedures: randPar
Generation of randomization sequences: genSeq
Assessment of randomization sequences: assess
Comparison of randomization sequences: compare
Other issues: chronBias
, combineBias()
, corGuess
, imbal
, selBias
, setPower()
Useful links