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Last update: doc. RNDr. Bohumír Procházka, CSc. (28.05.2008)
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Last update: doc. RNDr. Bohumír Procházka, CSc. (28.05.2008)
The course is intended to provide students with an introduction to the principles of modern biostatistical methods and their applications in medicine, epidemiology and biomedical research. The emphasis is on interpretation and concepts rather than calculations or mathematical details. An objective is to provide students with an ability to read the scientific literature in order to critically evaluate study designs and methods of data analysis. Basic concepts of statistical inference including hypothesis testing, p-values, and confidence intervals will be introduced. Specific topics will include comparisons of means and proportions, regression and correlation, measures of association, and confounding. Application to real data from various studies in public health and clinic research are used to illustrate the biostatistical methods. |
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Last update: doc. RNDr. Bohumír Procházka, CSc. (28.05.2008)
LITERATURE
ARMITAGE, P., BERRY, G. (1991). Statistical Methods in Medical Research. Blackwell Scientific Publications, Oxford. BEAGLEHOLE, R., BONITA, R., KJELLSTRÖM, T. (1993). Basic Epidemiology. WHO, Geneva. BRESLOW, N.E., DAY, N.E. (1980). Statistical Methods in Cancer Research, vol. 1 - The analysis of case-control studies. IARC, Lyon. BRESLOW, N.E., DAY, N.E. (1987). Statistical Methods in Cancer Research, vol. 2 - The design and analysis of cohort studies. COGGON, D., ROSE, G., BARKER, D.J.P. (1997). Epidemiology for the Uninitiated. BMJ Publishing Group, http://www.bmj.com/collections/epidem/epid.dtl COLTON, T. (1974). Statistics in Medicine. Little, Brown and Co., Boston. DALY, L.E., BOURKE, G.J., McGILVRAY, J. (1992). Interpretation and Uses of Medical Statistics. Blackwell Scientific Publications, Oxford. DANIEL, W.W. (1995). Biostatistics: A Foundation for Analysis in the Health Sciences. Wiley, New York. HENNEKENS, CH. H., BURING, J. (1987). Epidemiology in Medicine. Little, Brown and Co., Boston. JEWELL, N.P. (2004). Statistics for Epidemiology. Chapman & Hall/CRC, Boca Raton. KAHN, H.A., SEMPOS, CH. T. (1989). Statistical Methods in Epidemiology. Oxford University Press, Oxford. KIRKWOOD, B.R. (1992). Essentials of Medical Statistics. Blackwell Scientific Publications, Oxford. ROSNER, B.A. (1995). Fundamentals of Biostatistics. Duxbury Press, Belmont. ROTHMAN, K.J., GREENLAND, S. (1998). Modern Epidemiology, 2nd ed. Lippincott-Raven Publishers, Philadelphia. dos SANTOS SILVA, I. (1999). Cancer Epidemiology: Principles and Methods. International Agency for Research on Cancer, Lyon. SWINSCOW, T.D.V. (1997). Statistics at Square One. BMJ Publishing Group, http://www.bmj.com/collections/statsbk/index.dtl WASSERTHEIL-SMOLLER, S. (1990). Biostatistics and Epidemiology; a Primer for Health Professionals. Springer Verlag, N.York. WOODWARD, M. (2005). Epidemiology: Study Design and Data Analysis. 2nd ed. Chapman & Hall/CRC, Boca Raton. |
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Last update: doc. RNDr. Bohumír Procházka, CSc. (28.05.2008)
Seminars, practicals |
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Last update: doc. RNDr. Bohumír Procházka, CSc. (28.05.2008)
B i o s t a t i s t i c s - syllabus
3rd Medical Faculty, 2nd year, 1st term SEMINARS
1. Statistical concepts and terms
Historical remarks, statistics in medical sciences Logic of statistical reasoning (observations vs hypotheses) Important steps in the application of statistics Types of variables Descriptive statistics (location, variability) Probability, distribution Population - sample, sampling techniques Representativity of the sample Point and interval estimation, standard error Confidence interval
2. Statistical inference and testing (continuous variables)
Principles of statistical testing Statistical hypothesis and significance level One-sided and two-sided hypotheses One-sample, two-sample, and paired tests Parametrical and non-parametrical tests Testing hypotheses concerning the mean (t-test, Wilcoxon test) Introduction to multivariate methods, analysis of variance (ANOVA) Interpretation of results of statistical procedures
3. Statistical concepts used in epidemiology (categorical variables)
Contingency and 2-by-2 tables and methods for comparison of proportions Chi-square test, Fisher and McNemar tests, test for trend Basic types of studies used in epidemiology and related statistical models for their evaluation Vital statistics, rates and ratios Odds ratio, relative risk, attributable risk for cross-sectional, cohort, and case-control study Confounding, bias, precision Methods of standardization and stratification, Mantel-Haenszel technique Evaluation of diagnostic and screening tests (sensitivity and specificity, cut-off point)
4. Advanced statistical methods
Association between two variables: correlation, regression Advanced statistical methods in epidemiology logistic regression censored data survival analysis Mathematical tools for planning surveys and experiments, sample size determination
PRACTICALS
1. Statistical concepts: types of variables, probability distribution (binomial, Poisson, normal), population and sample, sampling methods, characteristics of location and variability, standard error, histogram, point and interval estimation, confidence interval
2. Statistical inference: testing statistical hypotheses, p-value, significance level Statistical tests for continuous variables: t-test and Wilcoxon test (one-sample, two-sample, paired), analysis of variance (ANOVA), F-test
3. Statistical tests for categorical variables: contingency table, chi-square test, McNemar test, test for trend Statistical methods in epidemiology: epidemiological measures of risk and corresponding confidence intervals, interpretation
4. Statistical association: linear regression, correlation, logistic regression Planning surveys: sample size determination Practical use of statistics: statistical packages, statistics in published papers |