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Last update: doc. Ing. Marek Omelka, Ph.D. (30.11.2020)
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Last update: doc. Ing. Marek Omelka, Ph.D. (10.06.2021)
To explain regression models for correlated and clustered data. |
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Last update: doc. Ing. Marek Omelka, Ph.D. (30.11.2020)
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. |
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Last update: doc. RNDr. Zdeněk Hlávka, Ph.D. (23.01.2023)
J.W. Hardin and J.M. Hilbe: Generalized Linear Model and Extensions. StataPress, 2007. J.W. Hardin and J.M. Hilbe: Generalized Estimating Equations. Chapman & Hall, 2003. P.J. Diggle, P.J. Heagerty, K.-Y. Liang, S.L. Zeger: Analysis of Longitudinal Data. Oxford University Press, 2nd edition, 2002.
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Last update: doc. RNDr. Zdeněk Hlávka, Ph.D. (26.01.2023)
Lecture + exercises. The faculty computing cluster can be used for more demanding data analyses and processing of large data sets. |
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Last update: doc. RNDr. Zdeněk Hlávka, Ph.D. (23.01.2023)
Requirements for the oral exam comprise the entire contents of the lectures and exercise sessions. |
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Last update: doc. RNDr. Zdeněk Hlávka, Ph.D. (23.01.2023)
Linear mixed effects model; Generalized linear mixed effects model; Generalized estimating equations. |
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Last update: doc. RNDr. Zdeněk Hlávka, Ph.D. (23.01.2023)
This course assumes mid-level knowledge of linear regression (both theory and applications) and good understanding of maximum likelihood theory. Knowledge of generalized linear models is recommended. |