[IV: Significance tests -- when to apply which one?].

Standard statistics software packages offer a variety of significance tests. The major problem, however, is the correct choice of an appropriate significance test for the underlying data and design setting. In general, the choice of significance tests should decide between two sample versus one sample (i.e. interindividual versus intraindividual) analyses; a further determinant is the clinical endpoint's scale level (mainly continuous or categorical). Two sample comparisons can be performed using the Wilcoxon test for continuous endpoints and the exact Fisher test for binary endpoints. Intraindividual comparisons become feasible using the sign test for continuous and the McNemar test for binary endpoints. Time to event data can be analysed using the log rank test. If one measurement series has to be compared to a single reference value, the sign test can be applied for continuous data, the binomial test for binary data.