At the end of this course, the students; 1) They will remember current basic knowledge of Biostatistics and learn and apply more advanced Biostatistics analysis. 2) They will gain basic and advanced skills in the calculation of sample and sample size used in the design and analysis of clinical studies, Logistic regression, survival analysis, multivariate regression models, multivariate ANOVA models, analysis of repeated measures and categorical data, statistical methods used in the evaluation of diagnostic tests.
MODE OF DELIVERY
Face to face
PRE-REQUISITES OF THE COURSE
Yes(SABE605)
RECOMMENDED OPTIONAL PROGRAMME COMPONENT
SABE 605 BIOSTATISTICS, SABE 606 RESEARCH METHODS
COURSE DEFINITION
In the Advanced Biostatistics Analysis course, students will develop the basic statistical skills they have gained in their current education. They will learn to apply Advanced Quantitative Methods and more advanced techniques to real data. They will learn to enter, organize, analyze, report and interpret their data using the SPSS package program.
COURSE CONTENTS
WEEK
TOPICS
1st Week
Recall of current statistical information and an overview of advanced Biostatistics methods in the literature and the necessity of these methods
2nd Week
Data cleaning and preparing data for analysis: Outliers, missing observations and coding, multi-option variables
3rd Week
An overview of the use of basic graphic methods and tables
4th Week
Analysis of Repeated Measurements (parametric and nonparametric methods)
5th Week
ANOVA Models: One-way, two-way analysis of variance models, generalized linear models (GLM), MANOVA models
Basic approaches on validity and reliability in studies using 10th Week Scales and examples of calculating scores from data
11th Week
Statistical methods used in the evaluation and decision making of Diagnostic tests: ROC Curve
12th Week
Basic approaches in calculating sample and sample size
13th Week
Randomization and methods in clinical trials
14th Week
Basic principles and mistakes in reporting and interpreting results
RECOMENDED OR REQUIRED READING
Course materials and notes, articles given in the course are sufficient.
PLANNED LEARNING ACTIVITIES AND TEACHING METHODS
Derslerin teorik kısmı power point sunusu şeklinde, uygulamaları ise SPSS 25.0 programı kullanılarak gösterilecektir. Lecture,Discussion,Questions/Answers,Practice,Proje,Problem Solving,Presentation yöntemleri uygulanacaktır.
ASSESSMENT METHODS AND CRITERIA
Quantity
Percentage(%)
Total(%)
0
Contribution of In-term Studies to Overall Grade(%)
0
Contribution of Final Examination to Overall Grade(%)
100
Total(%)
100
ECTS WORKLOAD
Activities
Number
Hours
Workload
Midterm exam
1
1
1
Preparation for Quiz
Individual or group work
14
10
140
Preparation for Final exam
1
10
10
Course hours
14
4
56
Preparation for Midterm exam
1
5
5
Laboratory (including preparation)
Final exam
1
2,5
2,5
Homework
Performance Practice
1
14
14
Article Presentation
1
10
10
Total Workload
238,5
Total Workload / 30
7,95
ECTS Credits of the Course
8
LANGUAGE OF INSTRUCTION
Turkish
WORK PLACEMENT(S)
No
KEY LEARNING OUTCOMES (KLO) / MATRIX OF LEARNING OUTCOMES (LO)