Statistical Issues In Planning Sampling Randomization and Blinding

The basics strategies of the RCT methodology are simple: appropriate patient sampling, choice of control group, randomization, and blinded assessment. However, each basic requirement can be satisfied in a myriad of ways, only some of which are valid in a particular RCT. What is ideal in one RCT may be either precluded or the worst choice in another. However, if all is done appropriately in the particular context of the RCT, nonrandom differences in response between the T and C groups reported as a statistically significant effect of T versus C are attributable to the treatment (thus the effect of T) rather than to biases in sampling, group assignment, measurement, or analysis.

Given that randomization is done to generate two random samples from the same population, any postrandomization removal of patients from the sample has the potential of biasing those samples relative to each other, and relative to the parent population. Consequently, RCT methodology also requires analysis of results by intention to treat. Every patient randomly assigned to a group (i.e., with the intention to treat) must be considered in the analysis comparing responses in the T and the C groups. In absence of an intention-to-treat analysis, when there is any postrandomization removal of patients from the randomized sample, the trial is no longer an RCT, because it is not based on comparison with randomized treatment and control groups. It is in this context that repeated measures of the primary outcome over the duration of treatment are particularly useful, for partial response data can be used to impute values for missing data or postdropout data, thus minimizing the associated loss of power.

To ensure that response is measured exactly the same in T and C groups, either objective outcome measures should be used or the assessor should be unaware of the treatment group to which a subject was assigned (i.e., "blinded").

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