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. 2014 Oct 7;20(37):13325–13342. doi: 10.3748/wjg.v20.i37.13325

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.