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patient he considers less desirable. In short, randomization alone, without
allocation concealment, is insufficient to eliminate selection bias and
ensure the internal validity of randomized clinical trials.
Lovell et al. [2000] describe a study in which four patients were
randomized to the wrong stratum; in two cases, the treatment re-
ceived was reversed. For an excruciatingly (and embarrassingly)
detailed analysis of this experiment by an FDA regulator, see
http://www.fda.gov/cber/review/etanimm052799r2.pdf.
Vance Berger and Costas Christophi offer the following guidelines for
treatment allocation:
•
Generate the allocation sequence in advance of screening any
patients.
•
Conceal the sequence from the experimenters.
•
Require the experimenter to enroll all eligible subjects in the order
in which they are screened.
•
Verify that the subject actually received the assigned treatment.
•
Conceal the proportions that have already been allocated (Schultz,
1996).
•
Conceal treatment codes until all patients have been randomized
and the database is locked.
•
Do not permit enrollment discretion when randomization may be
triggered by some earlier response pattern.
Blocked Randomization, Restricted Randomization, and
Adaptive Designs
All the above caveats apply to these procedures as well. The use of an
advanced statistical technique does not absolve its users from the need to
exercise common sense. Observers must be kept blinded to the treatment
received.
TO LEARN MORE
Good [2002] provides a series of anecdotes concerning the mythical Bum-
bling Pharmaceutical and Device Company that amply illustrate the results
of inadequate planning. See also Andersen [1990] and Elwood [1998].
Definitions and a further discussion of the interrelation among power
and significance level may be found in Lehmann [1986], Casella and
Berger [1990], and Good [2001]. You'll also find discussions of optimal
statistical procedures and their assumptions.
Shuster [1993] offers sample size guidelines for clinical trials. A detailed
analysis of bootstrap methodology is provided in Chapters 3 and 7.
For further insight into the principles of experimental design, light on
math and complex formulas but rich in insight, study the lessons of the
