Table 1.
Statistical methods adopted in the identification of biomarkers for pancreatic cancer
| Type of statistical method | Method adopted |
| Classical mono- and multi-variate methods | Student t-test (parametric) |
| Mann-Whitney U-test (non-parametric) | |
| T2 Hotelling | |
| ANOVA and MANOVA | |
| Bayes factors | |
| Unsupervised pattern recognition methods | Principal Component Analysis |
| Cluster Analysis | |
| Multidimensional Scaling | |
| Supervised classification methods | SIMCA |
| Ranking-PCA | |
| O-PLS | |
| CART | |
| Random Forests | |
| Methods for determining survival outcomes | Kaplan Meyer functions |
| Cox Regression | |
| Other methods | PAM |
| Metropolis algorithm and Monte Carlo simulation |
PCA: Principal component analysis; SIMCA: Soft independent model of class analogy; PLS: Partial least squares; CART: Classification and regression tree.