When and How to Interpret Null Results in NIBS: A Taxonomy Based on Prior Expectations and Experimental Design
Tom A. de Graaf; Tom A. de Graaf; Alexander T. Sack; Alexander T. Sack · 2018 · Frontiers in Neuroscience
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
The finding, in one line
“In conventional statistics, a positive result rejects that hypothesis, but a null result is meaningless.”
Abstract
Experiments often challenge the null hypothesis that an intervention, for instance application of non-invasive brain stimulation (NIBS), has no effect on an outcome measure. In conventional statistics, a positive result rejects that hypothesis, but a null result is meaningless. Informally, however, researchers often do find null results meaningful to a greater or lesser extent. We present a model to guide interpretation of null results in NIBS research. Along a “gradient of surprise,” from Replication nulls through Exploration nulls to Hypothesized nulls, null results can be less or more surpr
Abstract by Tom A. de Graaf; Tom A. de Graaf; Alexander T. Sack; Alexander T. Sack, Frontiers in Neuroscience (2018) — licensed CC BY 4.0.
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Metadata source: DOAJ · DOI 10.3389/fnins.2018.00915
