Statistical analyses ANCOVA

Statistical analyses (ANCOVA) showed that UHMWPE material (e.g., conventional versus crosslinked), displacement rate, and specimen geometry (e.g., smooth versus notched) all significantly influence the axial monotonic properties (yield stress and strain and ultimate stress and strain) [1-3]. In some cases, the interactions between these terms were also found to be significant for some of properties. The most important and influential of these was the interaction between specimen geometry and UHMWPE material. This implies that different UHMWPE formulations respond differently to the presence of a notch. 

Analysis of covariance (ANCOVA) employs both analysis of variance (ANOVA) and regression analyses in its procedures. In the present author s previous book Applied Statistical Designs for the Researcher), ANCOVA was not reported mainly because it presented statistical analysis that did not require the use of a computer. For this book, a computer with statistical software is a requirement hence, ANCOVA is discussed here, particularly because many statisticians refer to it as a special t5q>e of regression. 

Using several different statistical methods, for example, an unpaired t-test, an analysis adjusted for centre effects, ANCOVA adjusting for centre and including baseline risk as a covariate, etc., and choosing that method which produces the smallest p-value is another form of multiplicity and is inappropriate. 

Analysis of covariance (ANCOVA) reverses drug-induced depression of the CNS. Statistical method to determine if two or more related dependent variables exposed to two or more related variables differ significantly from chance. 

The name ANCOVA indicates that covariates are taken into account in the analysis. A covariate is a variable other than the main variable of interest. In the case of our ongoing example of examining decreases in SBP, subjects baseline SBP is likely to be of considerable interest. This technique of ANCOVA can be used to control statistically for baseline differences and to prevent them from skewing the results for the treatment effect. 

---