Course Description

THE RATIONALE

As a researcher whether you are working on 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.

Epidemiologists have depended on Stata for over three decades because of its specialized epidemiologic commands, accuracy, and ease of use.

THE COURSE OBJECTIVES:

By the end of this training, participants will be able to:

• Develop in-depth knowledge of measuring, reading and analyzing risk and disease incidence and prevalence.
• Improve basic statistical analytical skills in quality and explicit result presentation.

 THE COURSE OUTLINE

The course will cover the following:

MODULE 1: PRINCIPLES OF EPIDEMIOLOGY

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

MODULE 2: 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

MODULE 3: SAMPLE SIZE DETERMINATION

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

MODULE 4: 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

MODULE 5: 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

MODULE 6: COHORT DESIGN

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

MODULE 7: CASE CONTROL STUDIES

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

TARGET AUDIENCE

• The course is targeted at 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.

Delivery Method: Combines lectures, discussions, group exercises and illustrations

Venue:

Fee:

Duration: 1 week

Course Date: June 26th – 30th 2023