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Selected statistical methods in biomedicine

Code: 45673
ECTS: 5.0
Lecturers in charge: prof. dr. sc. Anamarija Jazbec - Lectures
Lecturers: prof. dr. sc. Anamarija Jazbec - Exercises
English level:


All teaching activities will be held in Croatian. However, foreign students in mixed groups will have the opportunity to attend additional office hours with the lecturer and teaching assistants in English to help master the course materials. Additionally, the lecturer will refer foreign students to the corresponding literature in English, as well as give them the possibility of taking the associated exams in English.

1. komponenta

Lecture typeTotal
Lectures 30
Exercises 15
* Load is given in academic hour (1 academic hour = 45 minutes)
COURSE AIMS AND OBJECTIVES: The aim of the course is to introduce students with statistical methods frequently used in biomedical science. The objective of the course is to teach students to independently compile, statistically analyze, present and analyze compiled data using SAS. To enable students to discuss and make conclusions based on already analyzed data. To introduce students to the possibility of various interpretations of the same problem analyzed in different ways.

ANOVA. One, Two and Three factors models. Modeling Interactions. Modeling Trend. Comparing using SAS.
Repeated Measure ANOVA. Experimental Design Basics. Between and Within subjects effects. Fixed and Random Effects.
Contingency Table Analysis. Sensitivity and Specificity of Diagnostic Tests. Positive and Negative Predictive Value. Likelihood ratio.
ROC (Receiver Operating Characteristic) Curves.
Survival analysis: The Survival Function and the Hazard Function for Continuous Random Variable. Parametric Methods.
The Survival Function and the Hazard Function for Discrete Random Variable. Right-Censored, Left-censored and Interval Censored Dana. Nonparametric Estimation. Residuals. Log-Rank and Wilcox on tests.
Cox Regression Model: The Proportional Hazards Model. Maximum Likelihood Estimation. Test of Adequacy of the Model. Proportion of Explained Variation (marginal, partial). Modeling Interactions. Difference Between Statistical and Biological Interaction. Choosing strategies.
Generalized Linear Models.
Logistic Regression.
  1. R. R. Sokal, F. J. Rohlf: Biometry
  2. J. K. Lindsey: Applying Generalized Linear Models
  3. C. S. Davis: Statistical Methods for the Analysis of Repeated Measurements
  4. J. P. Klein, M. L. Moeschberger: Survival Analysis, 2nd edition
  5. P. McCullagh, J. A. Nelder: Generalized Linear Models
  6. D. W. Hosmer, S. Lemeshow: Applied Logistic Regression, 2nd edition
  7. C. E. McCulloch, S. R. Searle: Generalized, Linear and Mixed Models
Prerequisit for:
Enrollment :
Passed : Mathematical statistics
Passed : Statistics lab 1
2. semester
Mandatory course - Regular study - Mathematical Statistics
Consultations schedule: