An<unk>  is a clinical<unk>  in which a single patient is the entire<unk> , a single case study. A<unk>  in which random allocation can be used to determine the order in which an experimental and a control intervention are given to a patient is an N of<unk>  randomized controlled<unk> . The order of experimental and control interventions can also be fixed by the researcher. This type of study has enabled practitioners to achieve experimental progress without the overwhelming work of designing a group comparison study. It can be very effective in confirming causality. This can be achieved in many ways. One of the most common procedures is the ABA withdrawal experimental design, where the patient problem is measured before a treatment is introduced (baseline) and then measured again during the treatment and finally when the treatment has terminated. If the problem vanished during the treatment it can be established that the treatment was effective. But the N=1 study can also be executed in an AB quasi experimental way; this means that causality cannot be definitively demonstrated. Another variation is non-concurrent experimental design where different points in time are compared with one another. This experimental design also has a problem with causality, whereby statistical significance under a frequentist paradigm may be un-interpretable but other methods, such as clinical significance or Bayesian methods should be considered. Many consider this framework to be a proof of concept or hypothesis generating process to inform subsequent, larger clinical<unk> s.
N of 1 trial
Multiple baseline design
Real world data
Natural history group
Clinical endpoint
Solomon four-group design
Blinded experiment
AllTrials