Null Hypothesis Significance Testing,p-values, Effects Sizes and Confidence Intervals
| Autor: | Michael Perdices |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Actuarial science
Cognitive Neuroscience 05 social sciences 050401 social sciences methods 050301 education Context (language use) Confidence interval Holy Grail Speech and Hearing Behavioral Neuroscience Neuropsychology and Physiological Psychology 0504 sociology Neurology Neurology (clinical) Association (psychology) Psychology 0503 education Statistical hypothesis testing |
| Zdroj: | Brain Impairment. 19:70-80 |
| ISSN: | 1839-5252 1443-9646 |
| DOI: | 10.1017/brimp.2017.28 |
| Popis: | There has been controversy over Null Hypothesis Significance Testing (NHST) since the first quarter of the 20th century and misconceptions about it still abound. The first section of this paper briefly discusses some of the problems and limitations of NHST. Overwhelmingly, the ‘holy grail’ of researchers has been to obtain significantp-values. In 1999 the American Psychological Association (APA) recommended that if NHST was used in data analysis, then researchers should report effect sizes (ESs) and their confident intervals (CIs) as well asp-values. The APA recommendations are summarised in the next section of the paper. But as neuropsychological rehabilitation clinicians, the primary interest is (or should be) to determine whether or not the effect of an intervention is clinically important, not just statistically significant. In this context, ESs and their CIs provide information relevant to clinicians. The next section of the paper reviews common ESs and worked out examples are provided for the calculation of three commonly used ES (Cohen'sd, Hedge'sgand Glass’delta). Web-based resources for calculating other ESs and their CIs are also reviewed. |
| Databáze: | OpenAIRE |
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