The services offered in Statistics are described below:

Experimental design

Design of experiments and their methodology based on the available samples and the data that can be obtained. Sample size / statistic power calculation.

Study monitoring

Verification of data quality. Estimation and elimination of bias.

Result analysis

Preparation of reports adapted for publication with their statistical analysis and interpretation of results.

Advisory service

Advice on statistical techniques and data treatment. In addition to support the appropriate statistical methodology taking into account the aspects of Bioethics according to the current legislation.

Statistical techniques.

• Classic statistics:
  1. Parametric tests.
  2. Non-parametric tests.
  3. Multiple comparisons.
  4. Exploratory analysis.
• Study design:
  1. Sample size estimation.
  2. Methodologic counselling.
  3. Optimisation of the statistical power.
• Statistic modelling:
  1. Predictive models.
  2. Inference models.
  3. Logistic regression, poisson, gamma...
  4. Multivariate analysis.
• Survival analysis:
  1. Kaplan-Meier.
  2. Proportional hazards model
• Omic data analysis:
  1. FDR and q-values calculation.
  2. Partial least squares (PLS y PLS-DA).
  3. LASSO.
  4. Elastic Net.
  5. Significance Analysis of Microarrays (SAM).
• Machine Learning:
  1. Neural networks.
  2. Support vector machine.
  3. Random Forest.
  4. Boosting and bagging.
• Non-supervised analysis:
  1. Clustering techniques.
  2. Main components (PCA).
• Resampling methods:
  1. Bootstrapping.
  2. Cross-validation.
  3. Permutation test.
• Bayesian inference.
• Others:
  1. R programming.
  2. High quality graphics preparation.
  3. Simulation studies
  4. Meta-analysis