singlehypothesis

Singlehypothesis refers to an approach in research and statistics that centers on testing a single primary hypothesis, rather than conducting a broad set of independent tests. The term is not universally standardized, but is used in methodological discussions to describe a focused hypothesis-driven design.

In statistical practice, singlehypothesis involves specifying one null hypothesis (H0) and one alternative hypothesis (H1) before data collection. In traditional significance testing, a predefined alpha level governs the decision rule for rejecting H0 based on a test statistic or p-value. When a study truly tests only one hypothesis, the concern about inflated Type I error from multiple comparisons is reduced, though issues can still arise if the study measures many endpoints or conducts unplanned analyses.

Singlehypothesis is often associated with preregistration and a clear analysis plan to deter p-hacking and HARKing (hypothesizing after results are seen). In Bayesian frameworks, the single hypothesis can be evaluated against alternatives using factors like the Bayes factor, offering an evidence-based comparison.

Advantages of singlehypothesis include simplicity, straightforward interpretation, and easier power calculation. Disadvantages include the potential to overlook other important effects, overconfidence in a narrowly specified claim, and reduced flexibility for exploratory research.

Examples include a randomized clinical trial testing whether a drug has any effect versus placebo, or an experiment testing a specific prediction of a theoretical model. See also null hypothesis, hypothesis testing, preregistration, multiple comparisons, and Bayes factor.