ANOVA analysis

FIGURE 11.3 One-way ANOVA (analysis of variance). One-way analysis of variance of basal rates of metabolism in melanophores (as measured by spontaneous dispersion of pigment due to G,.-protein activation) for four experiments. Cells were transiently transfected with cDNA for human calcitonin receptor (8 j-ig/ml) on four separate occasions to induce constitutive receptor activity. The means of the four basal readings for the cells for each experiment (see Table 11.4) are shown in the histogram (with standard errors). The one-way analysis of variance is used to determine whether there is a significant effect of test occasion (any one of the four experiments is different with respect to level of constitutive activity). 

METH-induced changes in neuropeptide levels, selective Dj (SCH 23390) and D2 (sulpiride) dopaminergic receptor antagonists were coadministered. The results are expressed as percent of control to facilitate comparisons each value represents the mean SEM of five to seven animals. Data were subjeeted to either a Student s r-test (figures 4 and 5) or ANOVA analysis followed by a multiple comparisons test (figures 1, 2, and 3). Signifieanee was set at the. 05 level. 

The total error has to be calculated here in different way compared with robustness. Whereas in (i) of-A is the variance within a laboratory, o kA is the variance between laboratories plus that within the laboratories, °ijkA = °k + °ijA- The interpretation is analogous to (i), if F < F( a>Vl>V2, then the null hypothesis cannot be rejected and the procedure can be considered as to be rugged. Advantageously, the test can be carried out by schemes of ANOVA (analysis of variance) as given in Sect. 5.1.1. 

Statistical analysis Each sample was taken in at least 5 replicates. The statistical analysis of the photosynthetic efficiency (Fv/Fm) of the species that were examined was performed using a one way-ANOVA analysis. 

ANOVA (Analysis of Variance) A statistical procedure that is used (a) to test for significant differences among means of several sets of results or (b) to estimate variances of several influences operating independently. 

ANOVA (ANalysis Of VAriance) provides a formal statistical procedure for analyzing the data arising from the experimental design used here (Table 3). 

ANOVA (analysis of variance), commercial experimental design software compared, 8 398t Anoxic conditions, defined, 3 757t ansa-metallocenes, 16 90, 94 ansa-zirconocene catalysts,... 

ANOVA analysis of variance COW correlation optimized warping... 

Hernandez and Rutledge (1994) investigated, by low resolution pulse NMR, the evolution of solid fat content (SFC) at 27.5 °C of cocoa masses of various geographical origin. The ANOVA analysis of a few quantitative parameters correlated with solid content and the speed of its transition from decomposition of fusion curves which indicated that the... 

Hence, hypothesis testing (ANOVA analysis followed by multiple comparison analysis) was used to determine NOEC and LOEC values expressed as % v/v of effluent. In order to satisfy statistical analysis requirements enabling NOEC and LOEC determinations, some bioassay protocols were adjusted to make sure that there were at least three replicates per effluent concentration and at least five effluent concentrations tested. TC % effluent values were then determined as follows ... 

Mann-Whitney Rank Sum Test, Sigmastat v 2.0 2 PERE = Potential Effluent Related Effect 3 ANOVA Analysis, a = 0.05 4 Canadian EEM database, unpublished data 5 not available, not applicable or not calculated 6 % PERE = Percent Potential Effluent Related Effect Observed = no. of expected effects divided by no. of endpoints calculated and multiplied by 100 7 LTF = lab-to-field. 

As we know from the section on ANOVA (analysis of variance see Section 2.3) in univariate cases, where only one feature is investigated, the sum of the squares of deviations of all n measuring values from the total mean is split into a part determined by... 

In the previous section, the duplicate-replicate control data set was used to give graphical representation of sampling and analytical variability. A statistical procedure referred to as analysis of variance (ANOVA) analysis can be done on the same data set to give a more quantitative statement on variability. Sinclair (1983) describes this method that compares variations that arise from different identifiable sources,... 

The G-BASE project has used several statistical packages to perform this nested ANOVA analysis (e.g., Minitab and SAS). It currently uses an MS Excel procedure with a macro based on the equations described by Sinclair (1983) in which the ANOVA is performed on results converted to logio (Johnson, 2002). Ramsey et al. (1992) suggest that the combined analytical and sampling variance should not exceed 20% of the total variance with the analytical variance ideally being <4%. 

Ae Amount of drug excreted unchanged in urine ANOVA Analysis of variance AUC Area under the curve... 

ANOVA Analysis of variables (factorial analysis of variables)... 

Results of the ANOVA analysis (the sum of squares type III was used to perform the analysis) are summarized in Table 4.5.4. 

In the Kruskal-Wallis test the original scores are first ranked and an ANOVA analysis is then carried out on the ranks. As with Wilcoxon s rank sum test, ranking of the observations must deal with ties. The sums of squares are based on... 

The most significant parameters were selected by ANOVA analysis (not shown). Correlation, mainly for the sulfury note, between the perception parameters derived from the TI cinves and parameters derived from the m>ma release curves are presented in Figure 6. The sensory characteristics of die sulfijry note were denoted by the initial letter (S) while die aroma release of individual compounds is denoted by a number which relates to the m/z value. PCI seemed to represent the sulfury characteristic axis. Time and area parameters, which were related to die most intense parts of the TI curves, were represented on the positive part of PCI while the decrease rates of sulphur components were on die opposite end of the axis. PC2 seemed representative of methylketone (die ions at m/z 143 and 1 IS are 2-nonanone and 2-heptanone respectively) but they did not relate to any perception parameter. 

Traditional (ANOVA) analysis of analgesic clinical trials (i.e., testing the null hypothesis when comparing treatment and placebo groups) have dealt inadequately with the complexities of pain relief data collected in these studies (3, 15). When patients have required rescue medication before the end of the study, scores of unobserved subsequent pain and pain relief (PR) scores have historically been imputed according to predetermined rules such as the so-called last observation... 

A common concern for a group sequential trial utilizing repeated interim ANOVA analysis is an inflated chance of observing a spurious result leading to an inflated Type I (false positive) error rate. Table 31.1 (24) illustrates the impact on the Type I error rate (a) based on the number of interim analyses each controlled at a = 0.05. 

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