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Making 'null effects' informative: statistical techniques and inferential frameworks
Being able to interpret ‘null effects?is important for cumulative knowledge generation in science. To draw informative conclusions from null-effects, researchers need to move beyond the incorrect interpretation of a non-significant result in a null-hypothesis significance test as evidence of the abs...
Autores principales: | Harms, Christopher, Lakens, Daniël |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Whioce Publishing Pte. Ltd.
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6412612/ https://www.ncbi.nlm.nih.gov/pubmed/30873486 |
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