TY - CHAP
M1 - Book, Section
TI - Chapter 6. What Does "Not Significant" Really Mean?
A1 - Glantz, Stanton A.
PY - 2012
T2 - Primer of Biostatistics, 7e
AB - Thus far, we have used statistical methods to reach conclusions by seeing how compatible the observations were with the null hypothesis that the treatment had no effect. When the data were unlikely to occur if this null hypothesis was true, we rejected it and concluded that the treatment had an effect. We used a test statistic (F, t, z, or χ2) to quantify the difference between the actual observations and those we would expect if the null hypothesis of no effect were true. We concluded that the treatment had an effect if the value of this test statistic was bigger than 95% of the values that would occur if the treatment had no effect. When this is so, it is common for medical investigators to report a statistically significant effect. On the other hand, when the test statistic is not big enough to reject the hypothesis of no treatment effect, investigators often report no statistically significant difference and then discuss their results as if they had proven that the treatment had no effect. All they really did was fail to demonstrate that it did have an effect. The distinction between positively demonstrating that a treatment had no effect and failing to demonstrate that it did have an effect is subtle but very important, especially in the light of the small numbers of subjects included in most clinical studies.*
SN -
PB - The McGraw-Hill Companies
CY - New York, NY
Y2 - 2022/05/26
UR - accessbiomedicalscience.mhmedical.com/content.aspx?aid=57414704
ER -