Using Bayes to get the most out of non-significant results¶
Dienes, Z. (2014). Using Bayes to get the most out of non-significant results. Frontiers in Psychology.
Cited by¶
1 citation across 1 artifact.
Each citation links to the sentence it supports in the citing article.
Domain-specific¶
- Bayes Factor
- Statistics — the home turf: Bayesian model comparison, replacing or complementing frequentist hypothesis tests and supplying gradable evidence for a null. Cognitive psychology — the Bayesian-replication movement reports it precisely because null evidence is gradable rather than an inconclusive non-result
This sourceArgues the case the sentence rests on: a Bayes factor distinguishes data that positively support the null from data that are simply insensitive, which a non-significant p-value cannot do.
SupportedVerified against the source
- Statistics — the home turf: Bayesian model comparison, replacing or complementing frequentist hypothesis tests and supplying gradable evidence for a null. Cognitive psychology — the Bayesian-replication movement reports it precisely because null evidence is gradable rather than an inconclusive non-result
Verification¶
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Registry ID ref:2054d50ed3ba · see in the full table