Friday, 21 September 2012

Randomisation methods

I'm not going to discuss the rationale for randomisation in trials in any detail here. Basically it will prevent selection bias, provide (in theory) comparable groups and maximise the precision of the estimates of intervention effects. What I have been more interested in is 'which allocation procedure should I be using?'

Essentially the options are:
  • Simple randomisation
  • Block randomisation
  • Stratified randomisation
  • Minimisation
A concise summary and explanation of these different methods are provided by the CONSORT Group and can be found here

In the pilot study I used simple randomisation which was easy to implement but limited in the sense that comparable study arms cannot be guaranteed with relatively small numbers of participants. In the pilot there were just 32 participants and so the probability of significant chance imbalances across the 2 arms was high. This is also likely in the main study where n=130 (based on sample size calculation following the pilot and still not considere a large RCT) and is further confounded by the fact that there are a number of important variables that are likely to be correlated to the study's main endpoints. These include gender, age, spatial ability, preferred learning style and stage of training programme. Basically it is important to ensure that these factors are as equally balanced as possible across the control and intervention groups.

This leaves stratified randomisation or minimisation as potential options.  Stratification, with restricted, block randomisation, is common in very large multi-centre clinical trials.  Unfortunately, where there are a number of strata and overall sample size is small it can lead to sparse/empty data in 'cells' and defeat the purpose of using startification in the first place.  In my study there are a number of important strata (as identified above) and the International Conference on Harmonization suggest that no more than 3 or 4 strata should be used in a clinical trial so this method is probably unsuitable.

This leaves minimisation (as originally presented by Pocock and Simon in 1975).  Minimisation is a dynamic process that ensures balance between groups for a number of important variables.  After true random allocation of the first participant, subsequent ones are allocated such that the imbalance of identified factors is minimised between the 2 groups.  Ideally a random component is also introduced at this point with heavy weighting in favour of the allocated intervention (e.g. with a probability of 0.8). The general procedure for allocating intervention group is summarised within this PPT on randomisation methods (slides 32-36).

In my study there will likely be 5 stratification factors as earlier highlighted: gender, age, spatial ability, preferred learning style and stage of training programme. Each of these factors will have levels associated with them - e.g. spatial ability would be categorised as high, middle or low and stage of programme would be 1, 2 or 3.

Minimisation is not strictly randomisation although it does incorporate randomisation within it. Furthermore it is accepted as a suitable alternative and some have argued it as superior (e.g. Treasure and MacRae 1998).

Minimisation IS relatively complex to manage and administer compared to other methods but given it's advantages in terms of reducing chance imbalances of important factors across my groups in what is a moderately sized study it should be the allocation procedure I adopt.

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