Article

Bayesian statistical methods have great potential advantages for the analysis of
data from single case designs. Bayesian methods combine prior information with
data from a study to form a posterior distribution of information about their
parameters and functions.
The interpretation of results from a Bayesian analysis
is more natural than those from classical methods, and there are interpretations
of useful quantities that are not possible in classical statistics, such as the
probability that an effect size is small, or is greater than zero, or is large
enough to be considered important. They are not based on asymptotic theory, so
small sample size is not a problem for inference. These methods are implemented
on free software, and are similar to non-Bayesian software, so analysts familiar
with frequentist methods for multilevel data should find the transition relatively painless.

Langue : ANGLAIS