Academic

   

Design and Analysis of Clinical Trials

Lecture Slides

Lecture 1

Lecture 2
Lecture 3
Lecture 4
Lecture 5
Lecture 6 Meta Analysis
Lecture 7 Statistical Analysis

Projects 

Project 1

Articles for project 1

Project 2

Reading

ICH-E9
Good Clinical Practice
Sample Clinical Trial Protocol
Reference Book
Reading Articles

Longitudinal Data Analysis

        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

Lectures

Lecture 1-2: Part I-Gaussian Longitudinal Data Analysis

Lecture 3-4: Part II - Non-Gaussian Longitudinal data Analysis 

Lecture 5 :   Part III-Missing Data Analysis in Longitudinal Studies 

Lecture 6 : Summary +Lab practice

Datasets  for the course demonstration 

Datasets for LDA course

Datasets Variable Descriptions  

Projects

Group Project I
Project I-datasets
Group Project II
Project II-Datasets

Sample SAS CODES

SAS Codes for two stage and LMM analysis

Sample SAS code

Sample R Codes

R-codes to analyze epileptic data

Reference books & Reading Materials

Books
1. Analysis of Longitudinal data (PJ. Diggle et al)
2.  Longitudinal Data Analysis (Hedeker & Gibbons) 
3.   LongitudinalData Analysis with Discrete and Continuous Responses

Articles

GEE using SAS

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Social and Economic Statistics

 Lecture Slides

Chapter One

Chapter Two

Chapter Three

Chapter Four 

Chapter Five 

Group Project

-To be available on Tuesday (Dec 17, 2019)

Biostatistics II

Lectures

Lecture 1 Categorical Data Analysis
Lecture 2  Basics on STATA

Lecture 3: Regression and Correlation
Lecture 4:  One-way ANOVA

Lecture 5:   Non-Parametric  Tests
Lecture 6:  Basics on Survival Analysis

Stata Codes

Sample Stata Codes  

Projects

Project I
Project II

Datasets for Project I

SOFTWARE

IBM SPSS 23 
Stata 14.2 Click Here.

Reference Books

1. Daniel W. (2008). Biostatistics Click Here.

2.  Balle G et al (2005). Biostatistics- A methodology for health Science. Click Here.

 

 

 

 

 Infectious Disease Modeling

1. General reading materials

2.  Individual assignment Articles

3. Assignment description 

3. Lecture slide, removed.

2017/18 Academic Year: Mathematics Students

Introduction to Statistics

1. Lecture slides

2. Assignments, Removed

 

2016/17 Academic Year: Geology Students

Statistics for geologist (Stat 2201)

1. Lecture slides

2. Worksheet

3. Group Assignment
4. Statistical Tables

2016/17 Academic Year

I. Introduction to statistics (Stat 2161)- AAU Informatics Students

1. Lecture Slides: Chapter 1-3

2. Lecture Slides: Chapter 4-6

3. Lecture Slides: Chapter 7

4. Assignment I

2016 Academic Year

1. Time Series Data Analysis- AAU Regular students

   1. To download chapter one and chapter two lecture notes click here

  2.  To download chapter three and chapter four lecture notes CLICK HERE
  3. To download chapter 5 lecture slides, Click here.
  4. To download chapter 6 lecture slides, Click here.
  5. To download the worksheet for time series data analysis CLICK HERE.
  6.  To download  the Box-Junkin note Click Here. 

2. Introduction to Probability (Stat 2082)-AAU Evening Students

  1. To download the class lectures for introduction to probability (Stat 2082) CLICK HERE

  2. To download lecture 3 and 4 slides click here
  3. To download lecture notes from chapter 1 to chapter 4, CLICK HERE!
  4. To download Assignment one, CLICK HERE!
  5. To download common integration and derivative rules, CLICK HERE.  
  6. To download lecture note for chapter five and six, CLICK HERE.
  7. To download lecture note for chapter seven and eight, CLICK HERE
  8.  To download the standard normal probability table (Ztable), CLICK HERE 

2. Introduction to Probability -AAU Computer Science Regular Students

1.  To download lecture note for chapter five and six CLICK HERE
2. To download lecture note for chapter seven and eight, CLICK HERE
3. To download the standard normal probability table (Z-table), CLICK HERE 

4. Linear Statistical Models- DBU Biostat  MSc Students

    List of  Reading Materials

 A link to access the following reference reading materials were sent to your email address. If you face a problem in accessing them, let me know.

     1. Linear Statistical Models 
     2. Advanced regression Models 
     3. Linear Models by Searle 
     4. Linear Models with R 
     5. Applied Linear Models with SAS
     6. Categorical Data Analysis (3rd ed.)

2015 Academic Year

Course Material for postgraduate students.

Program: MSc Biostatistics 

 Course: Design and Analysis of clinical trials- Stat 541

Course Description:

  This course covers the principles of therapeutic research design, including design of study, drug risk assessment, protocol writing, and methods of data analysis. Specifically, the course covers the following topics  

• Understand some frequently used terms in clinical trials

• Identify and classify different types of trial designs when reading a clinical trial report

• Understand the essential design issues of randomized clinical trials

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

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

•  Understand how to write protocols for clinical trial

•     Principles of drug risk assessment in the context of therapeutic research

•    Understand the basic of Meta- Analysis in Clinical trial

•    Differentiate Bias, Random error and Confounding

•   Power and sample size determination

•   Repeated measures in clinical trials

1. Introductory note

 To download  the general introductory note CLICK HERE

2. Class lectures

1. To download class lecture 01 CLICK HERE

2. To download class lecture 02 CLICK HERE
3. To download class lecture 03 and lecture 04  CLICK HERE  

3. Reference  Book

You can download the reference books by clicking on the title of the book.

1.  Design and Analysis of clinical trials: Concepts and Methodologies, 2nd Ed.

2. Clinical Trials: A Practical Guide to Design, Analysis, and Reporting.

3. CLINICAL TRIALS: A Methodologic Perspective, 2nd ED.