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The decision rule in this case states that 'for a fixed significance value α, a sequence fails the statistical test if it's P value<α'.
The general perception is that, to achieve a fixed significance level and power, a group sequential test will require a larger maximum total sample size than required by the corresponding standard single-stage test because missing observations are possible under the group sequential test setting.
As expected, power increases with increasing sample size with a fixed significance level.
As expected, power increase with increasing sample size for a fixed significance level.
Figure 4 shows the sample size under different views of effect size with fixed significance level at 0.05.
In a clinical study, when the interest is to target the power for different effect sizes, sample size can be estimated to ensure that the endpoint with the smallest effect size is sufficiently powered with a fixed significance level <img src="http://journals.plos.org/plosone/article/asset?id=info?doi/10.1371/journal.pone.0005054.e018.PNG" class= inline-graphic"/>.
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When repeating the ANCOVAs adding "team" as a fixed factor, significance changed for only one sub-scale.
We used 2-tailed type 3 tests for fixed effects with significance level set at α = 0.05.
The significance of fixed income can be seen in another Smith chart, which underscores the impossibility of even having a positive rate of return unless you were 40% bonds.
Significance of fixed effects was examined through F-tests using the procedure 'anova' in R. To test for effects of habitat and display size on pollinator visitation rate to flowers, the lmer function of the 'lme4' package and a Poisson error distribution were also used.
Significance of fixed effects was tested using the Wald Test.
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CEO of Professional Science Editing for Scientists @ prosciediting.com