COURSE UNIT TITLE

: STATISTICAL METHODS IN CLINICAL TRIALS

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
IST 3166 STATISTICAL METHODS IN CLINICAL TRIALS ELECTIVE 3 0 0 5

Offered By

Statistics

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASSOCIATE PROFESSOR ÖZGÜL VUPA ÇILENGIROĞLU

Offered to

Statistics
Statistics(Evening)

Course Objective

Statistical Methods in Clinical Trials course was designed to familiarize students with the biostatistical methods for the design and analysis of applied research in the medical sciences.

Learning Outcomes of the Course Unit

1   Describing fundamental elements of clinical trials,
2   Distinguishing types of clinical trials,
3   Describing the clinical data set,
4   Describing some special methods which are used for clinical data,
5   Calculating and interpreting the measures which are used for describing data.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Review of Statistics (Data, Variable, Sample, Population, Statistic, Parameter)
2 Basic Concepts and Applications of Clinical Trials
3 Estimating and Comparing Means and Proportions in Clinical Trials
4 Study Designs (Experimental) and Clinical Trials (Phases of Clinical Trials) Advantages and Disadvantages of Clinical Trials
5 Avoidance of Bias in Clinical Trials (Patient and Control Groups, Placebo, Blinding, Randomization, Intention-to-treat)
6 Categories of Clinical Trials: Controlled Clinical Trials (Parallel Controls: Randomized and NonRandomized and External Controls)
7 Categories of Clinical Trials: Controlled Clinical Trials (Sequential Controls:Self-controlled and Crossover)
8 Uncontrolled Clinical Trials
9 Modelling Quantitative and Qualitative Outcome Variables (Linear Regression)
10 Modelling Quantitative and Qualitative Outcome Variables (Logistic Regression)
11 Modelling Survival Data (Cencored Data, The Survival Function, The Probability Density Function, The Hazard Function, Mean and Median Survival Time)
12 Estimating the Hazard Function (Parametric Probability Models: The Exponential Dist., The Weibull Dist., The Lognormal Dist.)
13 Estimating the Hazard Function (Nonparametric: Kaplan-Meier Estimation)
14 Comparing Two Survival Curves (The Logrank Test)

Recomended or Required Reading

Textbook(s):
1. Klein J., Moeschberger M., (2003) Survival Analysis, Second Edition, Springer, USA.
2. Woodward M. (2005). Epidemiology: Study Design and Data Analysis, Second Edition, Chapman&Hall.
Supplementary Book(s):
1. Dawson-Saunders B. and Trapp R. G. (2004). Basic and Clinical Biostatistics, Forth Edition, Appleton&Lange.
2. Kestenbaum B. (2009). Epidemiology and Biostatics: An Introduction to Clinical Research, Springer.

Planned Learning Activities and Teaching Methods

Lecture , homework and problem solving.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 ASG ASSIGNMENT
3 FIN FINAL EXAM
4 FCG FINAL COURSE GRADE MTE * 0.40 + ASG * 0.10 + FIN * 0.50
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.40 + ASG * 0.10 + RST * 0.50


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

Exams and homeworks

Language of Instruction

English

Course Policies and Rules

Attendance to at least 70% for the lectures is an essential requirement of this course and is the responsibility of the student. It is necessary that attendance to the lecture and homework delivery must be on time. Any unethical behavior that occurs either in presentations or in exams will be dealt with as outlined in school policy. You can find the undergraduate policy at http://web.deu.edu.tr/fen

Contact Details for the Lecturer(s)

Dr. ÖZgül VUPA ÇILENGIROĞLU
DEU Faculty of Sciences, Department of Statistics
e-mail: ozgul.vupa@deu.edu.tr
Tel: 0232 301 86 02

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 3 42
Preparations before/after weekly lectures 14 3 42
Preparation for midterm exam 1 10 10
Preparation for final exam 1 20 20
Preparing assignments 2 6 12
Midterm 1 4 4
Final 1 4 4
TOTAL WORKLOAD (hours) 134

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12PO.13PO.14
LO.1553445
LO.2553445
LO.355445
LO.4553435
LO.55553435