• sample size
• clinical trials

Sample size prediction is an essential topic in the documentation of biometrical considerations for grant applications and in trial protocols, which will be submitted to drug authorities; lacking information on intended sample sizes and the underlying statistical power often result in severe amendments or even rejection of the submission. Therefore, this editorial intends to increase flexibility of clinical investigators in the communication with biometrical consultants and administrative authorities concerning these planning aspects in clinical trials.

The most important determinants of sample size are the study design and the clinical end point's scale level. This text will consider two different strategies in design—the paired data approach and the two sample approach. Paired data designs refer to intraindividual comparisons. Consider, for example, the comparison of the activity duration of two licensed mydriatic agents. For each study subject the application of drug I is randomised to one eye, drug II to the other. Being able to intraindividually compare the substances, their differentation becomes more feasible than in an unpaired study design. The latter applies drug I to one group of people and drug II to a different group. It would suffer from additional interindividual variation between the study subjects. The paired design, however, eliminates this additional data variation in the first place and therefore allows for an immediate treatment comparison. This reduction in data variation results in a remarkable sample size reduction. The second topic to be determined during the planning phase of studies is the scale of the clinical end point. In principle, one can distinguish between continuous parameters (for example, intraocular pressure) and categorial ones (for example, “occurrence of postoperative subjective photic phenomena: none/slight/severe”). An important special case of categorial parameters is the binary end point (“therapeutic success: yes/no”), well known continuous parameters are the normally …