At a user-defined significance level of α (default 0.05), corresponding to the probability of false rejection, we reject the null hypothesis and infer that the topologies are not equally supported if P < α, or we fail to reject the null hypothesis and say that the topologies are equally supported if P ≥ α.
Classical procedures are always associated with particular error probabilities, e.g., the probability of a false rejection or acceptance, or the probability of an estimator falling within a certain range.
It can be seen from the previous equations that the joint probability of false rejection increases while the joint probability of false acceptance decreases when using the AND conjunction rule.
They maximize the probability of rejection, assuming that certain significant measurement error has been introduced into the measurements, while keeping the probability for false rejection less than a certain threshold.
However, in such multiple tests, the probability of false rejection of at least one null hypothesis can be high.
where and are the probabilities of false rejection and false acceptance, respectively.
It takes into account both the concern about multiple testing errors and the probability of a false rejection [20].
Thus, the probability for a false rejection of an active drug was less than 5% (study design according to Gehan, 1961), which makes a clinical activity with >20% response rate of irinotecan unlikely.
The fundamental prediction of the optimal threshold individual-level approach to nestmate recognition is a correlation between true and false rejections, because increasing the probability of correct rejection of non-nestmates increases the chance of false rejection of nestmates.
The decision threshold, Λ NP, is then set to adjust the tradeoff between rejecting pathological voices (false rejection) and accepting normal voices (false acceptance).
