Abstract
While the general principles of data analysis apply also to clinical trials, such trials have yet special features. First there are many sorts of variation factors such as institutes, severity of illness and cause germs, which are fixed and indicative factor within a trial but act as if they were noise in the actual clinical treatments. We describe for the model based approach to this problem the generalized linear models including the proportional hazards model, logistic regression and regression models for ordinal categorical data. It requires, however, a careful examination of the model before extending the result beyond the trial and in some cases the double-blind randomized design based approach is recommended, which is described in § 2. Next in the analysis of clinical trials mostly concerned are the nonnormal distributions and the method based on the rank data can be applied for the ordinal categorical data, and vice versa. The analysis of repeated measures is a developing field of which we introduce generalized multivariate analysis of variance approach, two-stage mixed effects model and nonlinear mixed effects model. Other important issues discussed are various kinds of multiplicity problems and proving equivalence of a new drug with the standard.
