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The course focuses on statistical metods in medicine and epidemiology as well as on practical aspects of
applying statistics in biomedical environment.
Last update: G_M (28.05.2013)
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To explain methods for analysis of medical experiments. Last update: T_KPMS (11.05.2015)
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The exercise class credit is necessary to sign up for the exam. The credit for the exercise class will be awarded to the student who hands in a satisfactory solution to each assignment by the prescribed deadline. The nature of these requirements precludes any possibility of additional attempts to obtain the exercise class credit. Last update: Zichová Jitka, RNDr., Dr. (23.04.2018)
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BRESLOW, N.E., DAY, N.E. Statistical Methods in Cancer Research, Vol. I: The analysis of case-control studies. International Agency for Research on Cancer: Lyon, 1980. BRESLOW, N.E., DAY, N.E. Statistical Methods in Cancer Research, Vol. II: The design and analysis of cohort studies. International Agency for Research on Cancer: Lyon, 1987. ESTEVE, J., BENHAMOU, E., RAYMOND, L. Statistical Methods in Cancer Research, Vol. IV: Descriptive Epidemiology. International Agency for Research on Cancer: Lyon, 1994. FRIEDMAN, L.M., FURBERG, C.D., DEMETS, D.L. Fundamentals of Clinical Trials. 4th Ed., Springer: New York, 2010. Last update: Kulich Michal, doc. Mgr., Ph.D. (19.02.2015)
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Lecture+exercises. Last update: T_KPMS (12.05.2014)
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Only for summer 2020: if conduct of an oral exam is impossible, exam can be performed by distant methods.
The exam is oral. Requirements for the oral exam comprise the entire contents of the lectures and exercise sessions. Last update: Kulich Michal, doc. Mgr., Ph.D. (30.04.2020)
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1. Descriptive epidemiology. 2. Case-control studies. Classical analysis methods. Confounding. 3. Stratified case-control studies. Mantel-Haenszel test and estimator. Logistic regression for stratified studies. 4. Paired case-control studies. Classical analysis methods, McNemar test. Conditional logistic regression for paired studies. 5. Cohort studies and their analysis, incidence modeling. Cox model, Poisson loglinear model, discrete Cox regression. 6. Clinical trials, principles of their design and analysis, group sequential monitoring. 7. Design of medical studies, sample size calculation, randomization methods. 8. Ethical, legal and administrative aspects of medical experiments.
Last update: Kulich Michal, doc. Mgr., Ph.D. (04.02.2018)
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This course assumes advanced knowledge of theoretical foundations and practical applications of linear regression, logistic regression, loglinear models, survival analysis (Nelson-Aalen estimator, Kaplan-Meier estimator, Cox model). Last update: Kulich Michal, doc. Mgr., Ph.D. (25.05.2018)
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