Training course on Epidemiology and Biostatistics with Stata

Training course on Epidemiology and Biostatistics with Stata will be significant to the trainees who wish to further their studies on Epidemiology and Biostatistics. It will equip the trainees with skills necessary in the data analysis especially using stata. The course will mostly involve practical work as the trainees will always have their hand on the laptop and the stata application simultaneously.

Duration

5 days.

Targeted Audience

The individuals who are supposed to attend the course are mostly the health professionals, biostatisticians, clinicians, physicians, researchers all from both the public and private institutions who require to apply meta-analysis.

Learning Objectives

By the end of the course the trainee should be able to:

• Know how to run their epidemiological analysis using stata.
• Report appropriately the results supplied by the stata
• Understand the concepts of additivity, confounding, independence, and interaction in the context of logistical model.
• Learn how to clean data, combine data files, and carry out basic data analysis
• Producing descriptive statistics, calculating confidence intervals, hypothesis testing and calculating odds ratios and relative risks.

Course Content

Module I: Epidemiology

• Introduction to epidemiologic thinking
• Sufficient/component cause theory of disease
• Hill’s causal criteria
• Logic and errors
• Effect measures
• Study designs
• Randomization using Excel
• Bias and confounding
• Random error and statistics
• Crude analysis
• Stratified analysis
• Standardization
• Sensitivity (bias) analysis
• Case-cohort study design

Module II: Biostatistics

• Logic of significance tests
• Choice of significance test
• Comparison of two independent groups
• Basics of power analysis
• More on levels of measurement
• Comparison of two paired groups
• Multiplicity and the Comparison of 3+ Groups
• Correlation
• Linear regression
• Logistic regression and dummy variables
• Survival analysis: Kaplan-Meier graphs, Log-rank Test, and Cox regression
• Confidence intervals versus p values and trends toward significance
• Pearson correlation coefficient with clustered data
• Equivalence and non-inferiority tests
• Validity and reliability
• Bland-Altman analysis
• One sample tests

Methodology

The instructor led trainings are delivered using a blended learning approach and comprises of presentations, guided sessions of practical exercise, web-based tutorials and group work. Our facilitators are seasoned industry experts with years of experience, working as professional and trainers in these fields.