Multivariate analysis tested for factors influencing survival.
Importantly, multivariate analysis tests controlled for diabetic therapy, diabetic polyneuropathy, serum creatinine, and levels of GGT, showed that Ang-2 remained significantly higher among diabetic subjects with macrovascular disease when compared to those without macrovascular complications.
A second strategy of multivariate analysis tested the three variables: change of tumour size with first treatment evaluation, the MSKCC risk score and osseous lesions with a 6-months landmark.
In these, multivariate analysis testing for differences in survival among statistically significant subgroups of FIGO stage, tumour size, depth in cervical wall, number of positive nodes, degree of lymph vascular invasion, pathological parametrial involvement, infiltration to vagina, ovarian metastases, and histological grade was carried out.
Analyses of factors associated with gain in knowledge included parametric tests (linear regression multivariate analysis, t-test and repeated measures ANOVA).
A multivariate analysis (F test) adopting a < 0.001 p-value cutoff identified 1,132 genes (global pt test p-value < 0.001) differentially expressed among the four groups (Table 1).
Variables were initially tested for significance using univariate analysis and significant variables introduced in a multivariate analysis to test for significance and to identify adjusted odds ratios.
Principal component analysis (PCA) and multivariate analysis (MANCOVA) test were also developed.
Finally, a multivariate analysis (MANCOVA) test was applied considering the effect of SNB, ANB, APDI, A′P′, ratio (A′6′/A′P′), overbite, lower anterior facial height, ratio facial height, maxillary posterior discrepancy, and sex (reduced by the PCA from the initial cephalometric variables) on the molar sagittal angulations (outcome variable).
We performed multivariate analysis to test the significance of 8q gain with regard to outcome.
