Design and Analysis of Clinical Trials

The main objective of this course is to provide basic concepts on the design and analysis of clinical trials, which aims to enable students to:

·          Understand frequently used terms in clinical trials

·          Identify  and classify different types of trial  designs when reading  a clinical trial article

·          Understand the essential  design issues of randomized  clinical trials

·          Justify  the use of Stratification, Blocking, and Blinding  in clinical trials

·          Understand how to write protocols  for clinical trials

·          Understand the basic of Meta-  Analysis in Clinical trial

·          Differentiate  Bias, Random  error and Confounding

·          Understand how sample size determination carried out in clinical trials

·         Understand the  basic  statistical principles,  concepts,  and  methods  for clinical  data  analysis  and reporting

NOTE: Lecture slides, articles related with the course, projects and reference books are available in the course webpage.

Longitudinal Data Analysis

Course Description

Studies in which data are collected repeatedly on a sample of individuals over time are common in the health, social, and behavioral sciences; agricultural and biological sciences; education; economics; and business. Questions of interest in the context of such longitudinal data often focus on patterns of change of outcomes of interest over time and on identifying factors that are associated with patterns of change in relevant populations of individuals.This course covers statistical models for drawing scientific inferences from longitudinal data. Topics include: longitudinal study design, exploring longitudinal data, linear and general linear regression models for correlated data, including marginal, random effects and transition models, and handling missing data.

Course Objective

       To provide theoretical concepts on fundamental statistical models and methods for the analysis of longitudinal data, and their implementation using SAS and R by considering real datasets.

 Prerequisite

•         Basic understanding on Generalized linear Models

•         Familiarity with SAS

-          How to read data from a file

-          How perform simple data manipulations

-          Basic use of simple procedures such as PROC GLM.

•         Familiarity with R

-          Data management in R

-          Installing packages (i.e. nlme,lme4,)

-          Fitting standard GLM models

NOTE: Lecture slides, projects, datasets and codes, and reference books and/or reading material are available in the course webpage.

Design and Analysis of Clinical Trials

        The main objective of this course is to provide basic concepts on the design and analysis of clinical trials, which aims to enable students to:

·          Understand frequently used terms in clinical trials

·          Identify  and classify different types of trial  designs when reading  a clinical trial article

·          Understand the essential  design issues of randomized  clinical trials

·          Justify  the use of Stratification, Blocking, and Blinding  in clinical trials

·          Understand how to write protocols  for clinical trials

·          Understand the basic of Meta-  Analysis in Clinical trial

·          Differentiate  Bias, Random  error and Confounding

·          Understand how sample size determination carried out in clinical trials

·         Understand the  basic  statistical principles,  concepts,  and  methods  for clinical  data  analysis  and reporting

NOTE: Lecture slides, articles related with the course, homework and reference books are available in the course webpage. 

Analysis of two-dimensional gel electrophoresis experiment to estimate protein abundance

International Conference on Mathematics and Statistics Education

 To download   the slides presented at the international conference on mathematics and statistics education CLICK HERE.

Multilevel Random and marginal models for Longitudinal data

  Annual Science Conference at Bahir Dar University

In order to download the slides concerning "Multilevel random and marginal models for longitudinal data" which was presented at the  3rd Annual Science Conference prepared by Bahir Dar University CLICK HERE.

Longitidunal Data Analysis

 Introduction to  Longitudinal Data Analysis for UoG Staffs

To download the materials presented on the "Longitudinal Data Analysis" Seminar Click Here