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Study designs within patient

The study design is an important element in assessment of quality protocols. The overall purpose of the study design is to reduce the variability or bias inherent in all research. Good study design will always address control methods that reduce experimental bias. These control methods will often include treatment blinding, randomization and between- or within-patient study designs. The Schedule of Assessments describes a schedule of time and events and provides a complete... [Pg.29]

The greatest difficulty with ascending-dose, within-patient designs is usually in treatment masking. Double-blind requirements have to take into account a wide variety of dose sizes, and that contemporaneous placebo formulations will be needed. Some studies of this type are hybridized with a crossover strategy (see below). Dose tailing at the end of the study may be viewed as the same... [Pg.108]

Thus, there is a point at issue here between those who believe that the problem of carry-over is potentially so devastating as to preclude within-patient studies and those who think that the predictive power of random-effect models in conjunction with appropriate within-patient designs is so great that the opportunity to conduct them must not be passed up. [Pg.321]

Figure 11.2 Illustration of the Armitage sequential analysis study design. Patients are paired, and one of each pair receives each alternative treatment. If the patient receiving treatment A does better than the one receiving treatment B (A > B), then the line moves upwards vice versa, if the patient receiving B does better than the one receiving A (B > A), then the line moves downward. If the treatments cannot be distinguished within a pair of patients, then the line moves horizontally. The critical boundaries (broken lines) are computed from prospective measures of a and fj (e.g. p = 0.05 and 80% power, respectively). The technique derives from an engineering control chart and, once again, can be adapted to more sophisticated forms, including limits on the study size for indeterminate results... Figure 11.2 Illustration of the Armitage sequential analysis study design. Patients are paired, and one of each pair receives each alternative treatment. If the patient receiving treatment A does better than the one receiving treatment B (A > B), then the line moves upwards vice versa, if the patient receiving B does better than the one receiving A (B > A), then the line moves downward. If the treatments cannot be distinguished within a pair of patients, then the line moves horizontally. The critical boundaries (broken lines) are computed from prospective measures of a and fj (e.g. p = 0.05 and 80% power, respectively). The technique derives from an engineering control chart and, once again, can be adapted to more sophisticated forms, including limits on the study size for indeterminate results...

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Within-patient design

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