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#nhst

1 post1 participant0 posts today
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Bjørn Sætrevik

Imagine you preregistered study with tests A and B for a directed hypothesis H, but did not specify one-tailed or two-tailed testing. Test A is in the predicted direction, but p = between .05 and .09. Test B is in the non-predicted direction, but p < .05. How do you report results?

· 2 people · Closed
#PreRegistration#OpenScience#NHST
Public
Dr Mircea Zloteanu 🌼🐝

#statstab #233 Conditional equivalence testing (CET rule)

Thoughts: Many might not know that there are several decision rules for equivalence test. This one is slightly different from TOST classic.

#equivalencetests #equivalence #rules #nhst

journals.plos.org/plosone/arti

journals.plos.orgConditional equivalence testing: An alternative remedy for publication biasWe introduce a publication policy that incorporates “conditional equivalence testing” (CET), a two-stage testing scheme in which standard NHST is followed conditionally by testing for equivalence. The idea of CET is carefully considered as it has the potential to address recent concerns about reproducibility and the limited publication of null results. In this paper we detail the implementation of CET, investigate similarities with a Bayesian testing scheme, and outline the basis for how a scientific journal could proceed to reduce publication bias while remaining relevant.
Public
Dr Mircea Zloteanu 🌼🐝

#statstab #186 Are Multiple Contrast Tests Superior to the ANOVA?

Thoughts: Focuses more on the statistical aspects of the comparison than the theoretical ones. But insightful for newbies.

#nhst #anova #ttest #errorcontrol
#typeI #pvalues

degruyter.com/document/doi/10.

De Gruyter · Are Multiple Contrast Tests Superior to the ANOVA?Multiple contrast tests can be used to test arbitrary linear hypotheses by providing local and global test decisions as well as simultaneous confidence intervals. The ANOVA- F -test on the contrary can be used to test the global null hypothesis of no treatment effect. Thus, multiple contrast tests provide more information than the analysis of variance (ANOVA) by offering which levels cause the significance. We compare the exact powers of the ANOVA- F -test and multiple contrast tests to reject the global null hypothesis. Hereby, we compute their least favorable configurations (LFCs). It turns out that both procedures have the same LFCs under certain conditions. Exact power investigations show that their powers are equal to detect their LFCs.
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