# Training on Epidemiological Data Analysis Using Stata

Project Management, Training

Start date

12/08/2019

End date

16/08/2019

## Overview

Epidemiologists have relied on Stata for over 30 years because of its specialized epidemiologic commands, accuracy, and ease of use. Whether you are researching infectious diseases, investigating exposure to pathogens, or studying chronic diseases, Stata provides the data management and statistical tools to support your research. It also gives you the ability to make publication-quality graphics so you can clearly display your findings.

Target Participants

The course is suitable for potential epidemiologists and biostatisticians and current researchers including clinicians, laboratory and social scientists. Participants should have knowledge of Basic Statistics and be familiar with the Statistical package Stata.

Course duration

5 days

Course Outline

Principles of Epidemiology

• Epidemiology: concepts and terminology
• Population and Samples
• Measuring disease :Incidence and prevalence
• Study Design
• Intervention studies o Cohort studies
• Case control studies
• Observational studies
• Measuring the risk factor
• Exercises

Basic analytical procedures

• Review of Stata software
• Basic concepts about data type and analysis
• Introduction to basic Statistical models used in epidemiology
• Chi-square,
• t-test,
• Mann-Whitney
• ANOVA, ANCOVA,
• simple and multiple linear regressions,
• logistic regression.
• Exercises

Sample size determination

• Sample size calculation,
• Sampling weight
• Statistical power
• Constructing valid comparison groups
• Exercises

Epidemiological tables

• 2 × 2 and 2 × 2 stratified table for longitudinal, cohort study, case–control, and matched case–control data
• Odds ratio, incidence ratio, risk ratio, risk difference, and attributable fraction
• Chi-squared, Fishers’s exact, and Mantel–Haenszel tests

Survival Analysis

• Analysis of duration outcomes
• Estimating the probability of survival
• Modeling survival as a function of covariates using Cox, Weibull, lognormal, and other regression models.
• Predict hazard ratios
• Exercises

Cohort Design

• Standard cohort analysis
• Sample weighting
• Adjustment of variance
• Parametric models: poisson regression, Flexible Parametric survival Models (FPM)
• Exercises

Case Control Studies

• Basic design concepts
• Selection of Cases
• Selection of Control
• Matching
• Odds ratio for case control
• Case cohort studies
• Exercises

Note: This course outline is for guidance purposes and will be customized according to the participant’s requirements.